Academic literature on the topic 'Key Productivity Indicators'
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Journal articles on the topic "Key Productivity Indicators"
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Niameshchuk, H., V. Bozhanova, V. Chala, and A. Hlushchenko. "The environmental and resource productivity as the key element of green economy in EU." IOP Conference Series: Earth and Environmental Science 915, no. 1 (November 1, 2021): 012018. http://dx.doi.org/10.1088/1755-1315/915/1/012018.
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Abstract The purpose of this study was to analyze the indicators of environmental and resource productivity of European countries to identify leaders and outsiders and study their trends over recent decades. The results of the analysis showed that the indicators are characterized by uneven development, due to the characteristics of countries and their green policies. The key indicators of the Europe 2020 policy have been used for the analysis, namely resource productivity, greenhouse gas emissions per capita, recycling rate of municipal waste, eco-innovation index, final energy consumption in households. Linear trends for the period 1995-2019 with indication of trend equations were constructed for each indicator. The slope of the functions has been analyzed in order to identify the dynamics of trends. According to the results of the analysis, all indicators except greenhouse gas emissions per capita were characterized by positive dynamics, ie increased. It has been determined that the problematic indicator for EU countries is final energy consumption in households, which requires further detailed research.
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Albala-Bertrand, J. M. "Structural Change behind GDP Growth Rates via Key Indicators: Chile 1996-2015." International Business Research 11, no. 8 (July 6, 2018): 38. http://dx.doi.org/10.5539/ibr.v11n8p38.
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This paper deals with the change of some aggregate structural indicators in Chile over the 20-year period 1996-2015. We first produce an accounting growth decomposition to assess the changes in the contribution of capital productivity, capital intensity and labour participation to the growth rate of output per capita as well as the growth rate of labour income participation in national income. We then combine an accounting growth decomposition with a standard production function growth accounting to assess the contribution of both capital productivity and capital intensity to total factor productivity (TFP). To complement the latter, we produce optimal estimates of incremental capital productivity and incremental income elasticity to capital by means of a linear programming exercise. Our main conclusion is that capital intensity, rather than capital productivity or labour participation, has been the main growth contributor. TFP has contributed in a decreasing way from positive to negative over our sub-periods, so adding to and subtracting from GDP growth over time, with the main positive contributor to TFP growth systematically being a proportion of capital intensity.
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Berglund, Anders, Johannes Blackne, and Niklas Jansson. "Proposing a Feedback System to Enhance Learning Based on Key Performance Indicators." International Journal of Quality Assurance in Engineering and Technology Education 3, no. 1 (January 2014): 1–14. http://dx.doi.org/10.4018/ijqaete.2014010101.
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This paper proposes a feedback system that is based on the self-evaluation of perceived productivity as a mechanism for detecting deviations in an engineering design student project. By monitoring key performance indicators, project members used feedback loops to recognize alarming patterns and act accordingly. The study is based on descriptive survey data that addressed three factors of influence: perceived productivity, perception of stage completion, and work-activity distribution. The productivity data was analysed by detecting patterns in the form of peaks and lows and by combining the patterns with qualitative data from observations and documented work activities. Measurements were taken every time the project team got together; 33 occasions during the course of the project, resulting in a total of 280 student responses for productivity (P) and completion (C) and 115 student replies for work activity distribution. The findings provide an extraction of peak values and low values that enables tracking of critical incidents. Through an in-depth activity log, each value was enriched with lessons learned about what took place and the consequences for the project, thus enhancing learning from past activities through systematic feedback sessions. The accumulated set of data provided distinguishable patterns for the project team to interpret. Over time this made student actions more proactive, activity execution more distinct and purposeful, and resource allocation in combination with feedback reflections more refined.
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Spahija, S., E. Shehi, and G. Guxho. "Evaluation of production effectiveness in garment companies through key performance indicators." Autex Research Journal 12, no. 2 (October 1, 2012): 62–66. http://dx.doi.org/10.2478/v10304-012-0012-x.
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Abstract Key Performance Indicators help an organisation to improve productivity and to evaluate its success. Improved productivity is an essential part of increasing the value-added services that companies can offer to clients and hence their competitiveness. By using Key Performance Indicators, a company can establish baseline figures against a number of important areas. They can be considered like a health check on a company or a diagnosis of where a company can improve its performance. The definition of what they are and how they are measured does not change often, but Key Performance Indicators may change as the organisation's goals change. In this paper we present and discuss the way to establish Key Performance Indicators to evaluate the production effectiveness of garment companies. The KPIs are being tested in several garment companies in Albania and actually implemented in 25 companies.
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Zhang, Lu, and Zhiyun Ouyang. "Exploring the Relationships between Key Ecological Indicators to Improve Natural Conservation Planning at Different Scales." Forests 10, no. 1 (January 5, 2019): 32. http://dx.doi.org/10.3390/f10010032.
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Biodiversity, regulating ecosystem services (RES), and vegetation productivity are key indicators to instruct natural conservation planning. Decision makers often hope that ecosystems can be protected by focusing on certain key indicators, which requires an understanding of the relationships between the indicators. Using individual case studies, many have argued that these indicators commonly have significant relationships. However, these relationships at different spatial scales are unclear. Therefore, in this study, biodiversity and ecosystem services are modelled by the ecological niche model, the universal soil loss equation, and the equation of water balance in two study areas at different scales. The influence of vegetation productivity on the spatial pattern of other ecological indicators in the two areas is examined by a spatial lag model. The contributions of the driving factors on biodiversity distribution at both scales are identified by a boosted regression tree (BRT) model. The results showed that at the fine scale, the spatial correlations were strongest for species richness, especially mammalian species richness, and water retention. However, biodiversity had no significant relationship with vegetation productivity. In contrast, at a coarser scale, the correlation was stronger between plant diversity and regulating ecosystem services. In addition, plant diversity was significantly correlated with vegetation productivity. These differences between scales were controlled by various explanatory variables. At the fine scale, biophysical and climatic factors had the strongest effects on biodiversity distribution, while Net Primary Productivity (NPP) and ecoregion also had relatively high influences on biodiversity at the coarse scale. This demonstrates the critical importance of spatial scale in selecting conservation indicators. We suggest that rare mammalian species richness or flagship mammal species are suitable as conservation surrogates in fine-scale conservation planning. However, at a coarser scale, selecting vegetation patches with more rare plant species and high productivity for each ecoregion is a workable alternative method for conservation planning.
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Телеев, Джамалутдин, and Dzhamalutdin Teleev. "ANALYSIS OF KEY PARAMETERS OF THE FUNCTIONING OF BUSINESS PROCESSES AS AN EMPIRICAL BASE OF ACCOUNTING AND ANALYTICAL MANAGEMENT." Russian Journal of Management 6, no. 4 (December 25, 2018): 1–5. http://dx.doi.org/10.29039/article_5ca760b7213b73.74562403.
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The article presents the results of the analysis of the dynamics of indicators of output of products, works, services, capital productivity and capital ratio, the level of depreciation of fixed assets in the context of economic activities. According to the results of the analysis, the influence of labor productivity and the introduction of new technologies on one of the main indicators of the business process functioning - the output of products, work-services. The necessity of a process of large-scale development and introduction of new technologies with the aim of increasing labor productivity, increasing capital productivity and, ultimately, increasing the output of new products due to qualitative factors has been determined.
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Mikhnenko, P. A. "Economic and statistical analyses of labor productivity growth at russian industrial enterprises: Key factors." Management Science 11, no. 2 (May 26, 2021): 6–23. http://dx.doi.org/10.26794/2404-022x-2021-11-2-6-23.
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Increasing labor productivity (LP) is an actual task of the Russian economy and management of enterprises. Today, the country has a growing productivity gap between the most efficient and lagging companies. The aim of the study is to identify the key factors which determine the magnitude and growth rate of this indicator in the interests of revealing promising areas and ways of managing its growth. The paper describes the analysis of financial and economic indicators that are factors of sustainable growth in LP at domestic industrial enterprises, leading in this indicator in the period 2017–2019. The methodological basis has been the provisions of the production factors and productivity theories. The research method is based on the theorem of statistical hypotheses. The object of this research has been 94 Russian leading companies in terms of LP growth under reviewing period. An economic and statistical model of LP growth factors has been developed and the conditional probabilities of hypotheses have been calculated that characterize the ranges of growth of this indicator upon the occurrence of events corresponding to an increase in the values of financial and economic indicators. The key factors and the ranges of their change are highlighted for four ranges of the productivity rate: small, moderate, high and record. It is shown that the determining factors of a low rate are a revenue growth in the range from –23 to 57%, a decrease in the duration of an operating cycle to –7% and a growth in asset turnover up to 37%. The factors of the record rate of LP growth are revenue gain in the range 97–297%; operating cycle reduction in the range from –42 to –88% and the turnover of assets gain in the range 114–342%. The capital-labor ratio gain is considered with low probability as a factor of the moderate or high LP gain in combination with an increase in revenue and asset turnover. High correlation of the operating cycle reduction and increase the asset turnover can serve as an indicator of LP increase programs success. The proposed approach allowed to identify significant factors of LP growth at leading companies that had not been obvious during applying a regression analysis.
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Streltsova, Darya Alekseevna. "Key performance indicators of production activity efficiency in the implementation of lean production methods in mechanical-engineering enterprises." Interactive science, no. 10 (44) (October 19, 2019): 51–56. http://dx.doi.org/10.21661/r-508275.
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The article is devoted to the consideration of methods of lean production in relation to mechanical-engineering enterprises; the main key indicators of efficiency, productivity and key performance indicators (KPI), their similarities and differences. The key performance indicators, the most preferred in the analysis and management of production at mechanical-engineering enterprises, are defined in the article.
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Schnellbach, P., and G. Reinhart. "Evaluating the Effects of Energy Productivity Measures on Lean Production Key Performance Indicators." Procedia CIRP 26 (2015): 492–97. http://dx.doi.org/10.1016/j.procir.2014.07.094.
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Trukhmanov, V. B., E. A. Pervushkina, A. A. Statuev, V. N. Belov, and A. M. Volodin. "System of key performance indicators as a method for executive decision-making." E3S Web of Conferences 296 (2021): 02003. http://dx.doi.org/10.1051/e3sconf/202129602003.
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Key performance indicators, KPI are a proven cutting-edge tool for process productivity and staff performance monitoring. Therefore, today it is possible to find the use of this tool in the most varied spheres and industries. However, the system implementation is a long and painstaking process, which requires financial, labor and time expenditures. But in case of its successful implementation, KPI technology will provide the balance of advantage for the company management and contribute to its growth. The article presents the selection mechanism of KPI system development and implementation methods. Using key performance indicators, the organization is able to manage the process and modify it, as well as define objectives for employees and motivate them to achieve their objectives. KPIs are based on measuring quantitative benefits. Control shall be based on comprehensive and reliable information about the company’s process productivity. This is the only way to take quick management decisions, make adjustments to the operation of processes that will contribute to the achievement of strategic objectives as a whole.
Dissertations / Theses on the topic "Key Productivity Indicators"
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Погорелова, Татьяна Алексеевна. "Оценка персонала – ключевой фактор менеджмента." Thesis, Национальный технический университет "Харьковский политехнический институт", 2013. http://repository.kpi.kharkov.ua/handle/KhPI-Press/39907.
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Elías, Zuloeta Fernando Arturo, Guerra Luis Miguel Rojas, and Rodríguez Junior Gonzalo Segura. "Implementación de los dashboard para mejorar la productividad de la obra: Rehabilitación de la protección del perímetro del terreno de la Universidad Nacional de Piura colindante con la margen izquierda del Río Piura." Master's thesis, Universidad Peruana de Ciencias Aplicadas (UPC), 2019. http://hdl.handle.net/10757/626140.
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El propósito de la presente investigación es Determinar si la implementación de los Dashboard permitirá mejorar la productividad de la obra “Rehabilitación de la protección del perímetro del Terreno de la Universidad Nacional de Piura colindante con la margen izquierda del Río Piura”. Para ello se ha investigado con respecto a dos variables: Implementación de Dashboards y Productividad.
El estudio partió de la hipótesis que la implementación de los Dashboards influye significativamente en la mejora de la productividad de la obra “Rehabilitación de la protección del perímetro del Terreno de la Universidad Nacional de Piura colindante con la margen izquierda del Río Piura. Para probar las hipótesis se utilizó el estadístico de prueba de T de Student.
En el estudio se trabajó con una muestra de 85 registros documentales, los cuales fueron obtenidos de la obra en mención, la recolección de datos se realizó mediante la técnica de la observación y análisis documental; con ello se pudo crear los indicadores de rendimiento o Kpi’s para la elaboración de los Dashboards. El diseño investigativo es Cuasi Experimental y longitudinal.
Como resultado se demostró que la implementación de los Dashboard influye significativamente en la mejora de la productividad del área de estudio, ello permitió tomar decisiones para mejorar productividad de la obra, como resultado final se redujo en 10% el costo total de la obra.The purpose of this research is to determine if the implementation of the Dashboard will improve the productivity of the work "Rehabilitation of the perimeter protection of the land of the National University of Piura adjoining the left bank of the Piura River." For this, it has been investigated with respect to two variables: Implementation of Dashboards and Productivity. The study started from the hypothesis that the implementation of the Dashboards significantly influences the improvement of the productivity of the work "Rehabilitation of the protection of the perimeter of the land of the National University of Piura adjoining the left bank of the Piura River. To test the hypotheses we used the Student's T test statistic. In the study we worked with a sample of 85 documentary records, which were obtained from the work in question, the data collection was made through the technique of observation and documentary analysis; with this it was possible to create the performance indicators or Kpi's for the elaboration of the Dashboards. The research design is Quasi Experimental and longitudinal. As a result it was demonstrated that the implementation of the Dashboard significantly influences the improvement of the productivity of the study area, this allowed to make decisions to improve the productivity of the work, as a final result the total cost of the work was reduced by 10%.
Trabajo de investigación
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Klingner, Stephan, Thomas Meiren, and Michael Becker. "Produktivitätsorientiertes Service Engineering." LIV, 2013. https://ul.qucosa.de/id/qucosa%3A11825.
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Der 39. Band der Leipziger Beiträge zur Informatik setzt sich mit den Herausforderungen im Zusammenhang mit der zunehmenden Industrialisierung der Dienstleistungswirtschaft auseinander. Eine hohe Komplexität der Dienstleistungsportfolios sowie eine zunehmende
Dienstleistungsorientierung ehemals rein produktionswirtschaftlich ausgerichteter Unternehmen bedürfen leistungsfähiger und angepasster Methoden und Werkzeuge. Voraussetzung dafür ist die präzise und umfassende Modellierung von Dienstleistungen,
die Berücksichtigung von Aspekten der Produktivität sowie die Entwicklung geeigneter Softwarewerkzeuge. Das vorliegende Buch beschäftigt sich mit diesen Herausforderungen und Fragestellungen und schlägt verschiedene Lösungsansätze vor.:Stephan Klingner
Produktivitätssteigerung durch komponentenbasierte Dienstleistungen – Ergebnisse eines Forschungsprojekts
Thomas Meiren, Sabrina Lamberth
Beschreibung und Strukturierung von Dienstleistungsan
geboten
Sabrina Lamberth
Dienstleistungsproduktivität – Grundlagen und Kennzahlen für die komponentenbasierte Produktivitätsbetrachtung von Dienstleistungen.
Stephan Klingner, Martin Böttcher
Der Begriff der Komponente als Grundlage von Konfigurationen in der Dienstleistungsdomäne
Michael Becker, Stephan Klingner
Metamodell zur komponentenbasierten Modellierung komplexer Dienstleistungen.
Michael Becker, Stephan Klingner
Abhängigkeitsbeziehungen zwischen Elementen von
Dienstleistungsportfolios
Michael Becker, Stephan Klingner, Frank Schumacher
Werkzeug zur komponentenbasierten Modellierung und Konfiguration von Dienstleistungen
Sabrina Lamberth, Thomas Meiren
Methodik zur produktivitätsorientierten Granularitätsoptimierung bei komponentenbasierten Dienstleistungen
Sabrina Lamberth
Methodik zur Analyse und Optimierung der Dienstleistungsproduktivität unter Berücksichtigung qualitativer Faktoren
Mike Freitag, Franz Pauthner, Stefan Ochs, Mathias Mayer
Entwicklung eines Frameworks zum Change Management für ECM-Lösungen
Ronni Swialkowski, Arndt Döhler
Komponentisierung des Full-Services E-Commerce Angebots bei Intershop
Till Post, Wilhelm Taurel
Aus der Praxis der Produktivität internationaler Hightech-Dienstleistungssysteme
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Pereme, Florian. "Augmentation de la productivité des projets de R&D sous-traités, sous fortes contraintes, une inférence des approches Earned value et agiles." Thesis, Strasbourg, 2019. http://www.theses.fr/2019STRAD022.
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Les entreprises de la technologie sont de plus en plus confrontées à des problématiques de R&D et d’innovation. L’accélération d’émergence et d’évolution des technologies met une pression forte et de nombreuses nouvelles contraintes sur la nécessité de réduire le cycle de vie de production ainsi que d’augmenter la productivité des départements de R&D. La première partie de ses travaux vise à caractériser de façon formelle l’ensemble des acteurs et leurs interactions dans le processus complexe de création d’innovation incluant la phase de R&D. Nous aboutissons à une définition plus claire des verrous qui posent des questions autour des processus de production de R&D dans un contexte industriel. Dans une seconde partie, nous prenons le parti de proposer une construction d’organisation de la R&D basée sur des méthodes ayant fait leurs preuves dans le monde du développement. En restant ancrés dans les caractérisations obtenues à la première partie des travaux, nous focalisons nos travaux de construction notamment sur les méthodes agiles qui se veulent plus flexibles et adaptatives car centrées sur les acteurs et les livrables plus que sur les processus, ainsi que sur le modèle Earned value comme outil de pilotage de mesure de la valeur produite. Après un état de l’art aussi bien externe que propre aux projets de l’ESN Altran Technologies, nous construisons un Framework original. Ce dernier définit une liste de principes. Cette approche permet à chacun d’intégrer et de déployer le modèle selon ses propres contraintes. La finalité n’est non pas de garantir une productivité d’innovation, ce qui nous semble impossible, mais bien d’augmenter, de maîtriser et de mesurer sa probabilité d’occurrence. La dernière partie conclut la proposition de framework en identifiant les avantages et les limites, et propose de futurs travaux dans une prospective des R&D de demain à long termeTechnology companies are more and more faced to R&D and innovation issues. The acceleration of emergence and evolution of technologies puts a lot of pressure and many new constraints that lead to the needs of lifecycle reduction and R&D productivity enhancement. The first part of this work aims to characterize formally all the actors and their interactions in the complex process of creating innovation that includes R&D phases. We lead to a clearer definition of the scientific locks and raise questions around R&D production processes in an industrial context. In a second part, we made the decision to propose an organizational construction for R&D structure based on proven methods in the world of system development. By remaining anchored in the characterizations obtained in the first part, we focus our construction work in particular on agile methods and on Earned value model. Agile methods are intended to be more flexible and adaptive caused they are focused on actors and deliveries and not onprocesses. Here we use the Earned value model as a management tool for measuring the produced value. After a state of the art both external and internal to the Altran Technologies contractor projects, we build an original framework. This last one defines a list of several principles. This approach allows each one to deploy the model in compliancy with own constraints. The final aim is not to guaranty innovation productivity because for us it seems almost impossible, but to increase, control and measure his occurrence probability. The last part closes the framework proposal by identifying the advantages and the limits, and proposes future perspectives of works to compare the method with some real projects
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Benediktsdóttir, Laufey. "A customer-centric evaluation of a smart manufacturing concept : Development of a continuous improvement strategy for improving the productivity of a small and medium-sized enterprises." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-267040.
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Nytt AB is a startup focusing on simplifying the concept of smart manufacturing to small and medium-sized companies providing an add-on machine monitoring solution for data analyzing. The product is currently under development with the final product soon to be launched. In the next phase of Nytt AB, a marketing plan has to be strategized. This thesis, which is built on previous Nytt AB’s work, focuses on addressing issues that will be important when creating a marketing and sales strategy. The customer is put as the focal point and the customer values analyzed including discussions on productivity improvements within the machines and how to standardize the changes to satisfy every customer. Using research questions as a base for the study, the customer values were analyzed by first understanding the main threats, weaknesses, strengths, and opportunities for the product and then analyzing data from an installed prototype and the improvements that can be achieved based on the data. The customers can, by using the product get statistical facts about their machines which can be the first step to understand the need for changes within their company. With future development, further customer values will appear, such as providing aid on how to improve KPIs such as availability. Providing this information to the customers will help them obtain a better insight into the field of smart manufacturing, the manufacturing of the future.Nytt AB är ett nystartat företag som fokuserar på att förenkla konceptet smart tillverkning för små och medelstora företag och erbjuder en maskinövervakningslösning för dataanalys. Produkten är just nu under utveckling, slutprodukten planeras lanseras snart. Nästa steg för Nytt AB är att strukturera en marknadsplan. Detta examensarbete, som bygger på tidigare arbete i Nytt AB, fokuserar på frågor som kommer att vara viktiga när man skapar en marknadsförings- och försäljningsstrategi. Kunden blir i fokus när kundvärdena är analyserade inklusive i diskussioner om produktivitetsförbättringar för maskiner och hur man standardiserar förändringarna för att uppfylla kundens krav. Med hjälp av forskningsfrågor, analyseras kundvärdena genom att först förstå de viktigaste hoten, svagheterna, styrkorna och möjligheterna för produkten och sedan analyseras data från prototypen och de förbättringar som kan uppnås baserat på given data. Kunderna kan genom att använda produkten få statistik om sina maskiner vilket kan vara första steget att inse behovet av förändringar inom kundföretaget. Vid utveckling kommer ytterligare kundvärden att dyka upp, till exempel metoder på hur man förbättrar olika nyckeltal, såsom tillgänglighet. Att ge denna information till kunderna hjälper dem att få en bättre inblick i smart tillverkning, framtidens tillverkning.
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Verrier, Brunilde. "Stratégie Lean and Green : roadmap d'analyse et de déploiement d'une politique de management alliant amélioration continue et développement durable en entreprise industrielle." Thesis, Strasbourg, 2015. http://www.theses.fr/2015STRAD017/document.
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Ces travaux de thèse s’intéressent à l’association des performances industrielles et environnementales avec une démarche d’amélioration continue orientée vers le développement durable et ciblent l’élimination conjointe des « gaspillages » Lean et Green dans les processus de fabrication. La problématique majeure réside dans la mise en place des outils L&G au sein d’entreprises manufacturières possédant des processus et caractéristiques culturelles variés. Basés sur une analyse suivie de l’état de l’art et d’enquêtes de bonnes pratiques, les travaux de recherche incluent plusieurs évaluations et observations sur sites industriels. La mise au point d’une roadmap de déploiement adaptable, mettant en valeur les aspects sociaux par le biais de l’implication et de la valorisation des employés, est ainsi complétée par un modèle de sélection d’indicateurs environnementaux, une « Maison du L&G » et un modèle de maturité particularisé pour le niveau d’implémentation de la stratégieThis thesis addresses the association of industrial and environmental performances with a continuous improvement approach oriented toward sustainable development, and particularly seeks for the identification and elimination of Lean and Green “wastes” in manufacturing processes. The major issue lies in the deployment of L&G tools within manufacturing firms with various processes and cultural characteristics. Based upon a thorough state of the art and industrial surveys on best practices, the research includes several assessments and observations on manufacturing sites. The development of an adaptable roadmap of deployment highlighting social concerns through the involvement of employees in improvements is therefore completed with a selection model of environmental indicators, a “L&G House” and a maturity model for the strategy’s implementation
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"Produktivitätsorientiertes Service Engineering." Universitätsbibliothek Leipzig, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-103786.
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Der 39. Band der Leipziger Beiträge zur Informatik setzt sich mit den Herausforderungen im Zusammenhang mit der zunehmenden Industrialisierung der Dienstleistungswirtschaft auseinander. Eine hohe Komplexität der Dienstleistungsportfolios sowie eine zunehmende
Dienstleistungsorientierung ehemals rein produktionswirtschaftlich ausgerichteter Unternehmen bedürfen leistungsfähiger und angepasster Methoden und Werkzeuge. Voraussetzung dafür ist die präzise und umfassende Modellierung von Dienstleistungen,
die Berücksichtigung von Aspekten der Produktivität sowie die Entwicklung geeigneter Softwarewerkzeuge. Das vorliegende Buch beschäftigt sich mit diesen Herausforderungen und Fragestellungen und schlägt verschiedene Lösungsansätze vor.
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Guimarães, Leandro Jorge Barros. "Implementação de um sistema de gestão de manutenção." Master's thesis, 2021. http://hdl.handle.net/10316/98237.
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Dissertação de Mestrado Integrado em Engenharia Mecânica apresentada à Faculdade de Ciências e TecnologiaA competitividade empresarial tem vindo a aumentar com o consequente aumento da concorrência, confrontando as empresas com a necessidade de evoluírem, existindo um conjunto de características que lhes permitem diminuir os custos e melhorar a qualidade dos produtos e serviços. A manutenção, quando bem exercida, surge como um fator estratégico para garantir a máxima produtividade possível.A presente dissertação é resultado do trabalho desenvolvido em parceria com a AMOB Group, empresa especialista na produção de equipamentos de curvatura de tubos e perfis, tendo como objetivo principal a implementação de um sistema de gestão de manutenção, também conhecido por CMMS (Computerized Maintenance Management System).Assim, procurou-se fazer um levantamento das necessidades seguido de uma análise da situação atual do método de gestão da manutenção praticado. Seguiu-se o levantamento do inventário fabril bem como a criação de um sistema de numeração dos equipamentos, definiu-se os planos de manutenção preventiva e elaborou-se um histórico dos equipamentos com base nos registos de manutenção existentes. Completos os passos anteriormente descritos, inseriu-se toda a informação no sistema ERP (Enterprise Resource Planning), a fim de despontar e iniciar a monitorização do programa. Por fim, ainda que não implementados, foram definidos os KPI’s (Key Performance Indicator) para o sistema, para que no futuro próximo se possam tomar decisões de gestão com apoio nestes. O acompanhamento e monitorização diária do sistema de gestão de manutenção, apesar de curto período, permitiu identificar diversos erros e problemas, comprometendo o funcionamento otimizado deste. Para este efeito, foram apontandos e reportados os erros encontrados à empresa fornecedora do software, de forma a ajustá-lo de encontro com as necessidades da empresa.
Business competitiveness has been increasing as a result of the rising competition, confronting companies with the need to evolve, with a set of characteristics that allow them to reduce costs and improve the quality of their products and services. Maintenance, when properly exercised, emerges as a strategic factor to ensure maximum productivity.This dissertation is the result of work developed in partnership with the AMOB Group, a company specialized in the production of bending equipment for tubes and profiles, with the main objective being the implementation of a maintenance management system, also known as CMMS (Computerized Maintenance Management System).Thus, an attempt was made to carry out a survey of needs followed by an analysis of the current situation of the maintenance management method used. This was followed by a survey of the factory inventory as well as the creation of an equipment numbering system, preventive maintenance plans were defined and an equipment history was drawn up based on existing maintenance records.After that, all the information was inserted into the ERP (Enterprise Resource Planning) system, in order to emerge and start monitoring the program. Finally, although not implemented, the KPI's (Key Performance Indicators) for the system were defined, so that in the near future management decisions can be taken with their support. The support and daily monitoring of the maintenance management system, altough during a short period, allowed the identification of many gaps and technical problems, that were compromising the well functioning of the system. Therefore, inumerous technological failures and bugs were presented and reported to the software supplier, in order to adapt and adjust to the enterprise’s needs.
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Tsung-YuTung and 董宗諭. "Improving the Productivity Key Performance Indicator by Industry 4.0 Concept- Case of M Company Etching Machine." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/5us9b9.
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Хлопецька, О. О. "Формування мотивації персоналу підприємства як складова соціально-трудових відносин." Thesis, 2016. http://dspace.oneu.edu.ua/jspui/handle/123456789/6338.
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Мета дипломної роботи полягає в розробці на основі проведеного дослідження практичних шляхів вдосконалення мотивації праці в системі управління підприємством.Цель дипломной работы заключается в разработке на основе проведенного исследования практических путей совершенствования мотивации труда в системе управления предприятием.
The purpose of the thesis is to develop practical ways to improve the motivation of work in the enterprise management system based on the study.
Books on the topic "Key Productivity Indicators"
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Parmenter, David. Key Performance Indicators. New York: John Wiley & Sons, Ltd., 2007.
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Key performance indicators: Developing, implementing, and using winning KPIs. Hoboken, N.J: John Wiley & Sons, 2010.
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Asia Pacific Economic Cooperation (Organization). Human Resource Development Working Group., ed. Project on developing key performance indicators and productivity/performance benchmarks for performance based remuneration systems, Kuala Lumpur, Malaysia. [Singapore]: Asia-Pacific Economic Cooperation, 2007.
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Parmenter, David. Key Performance Indicators: Developing, Implementing, and Using Winning KPIs. Wiley & Sons, Incorporated, John, 2019.
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Parmenter, David. Key Performance Indicators: Developing, Implementing, and Using Winning KPIs. Wiley & Sons, Incorporated, John, 2019.
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Key Performance Indicators: Developing, Implementing, and Using Winning KPIs. Wiley & Sons, Incorporated, John, 2015.
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Key Performance Indicators: Developing, Implementing,and Using Winning KPIs. Wiley, 2007.
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Parmenter, David. Key Performance Indicators: Developing, Implementing, and Using Winning KPIs. Wiley & Sons, Incorporated, John, 2015.
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Parmenter, David. Key Performance Indicators: Developing, Implementing, and Using Winning KPIs. Wiley & Sons, Incorporated, John, 2010.
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Shengelia, Revaz. Modern Economics. Universal, Georgia, 2021. http://dx.doi.org/10.36962/rsme012021.
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Economy and mankind are inextricably interlinked. Just as the economy or the production of material wealth is unimaginable without a man, so human existence and development are impossible without the wealth created in the economy. Shortly, both the goal and the means of achieving and realization of the economy are still the human resources. People have long ago noticed that it was the economy that created livelihoods, and the delays in their production led to the catastrophic events such as hunger, poverty, civil wars, social upheavals, revolutions, moral degeneration, and more. Therefore, the special interest of people in understanding the regulatory framework of the functioning of the economy has existed and exists in all historical epochs [A. Sisvadze. Economic theory. Part One. 2006y. p. 22]. The system of economic disciplines studies economy or economic activities of a society. All of them are based on science, which is currently called economic theory in the post-socialist space (the science of economics, the principles of economics or modern economics), and in most countries of the world - predominantly in the Greek-Latin manner - economics. The title of the present book is also Modern Economics. Economics (economic theory) is the science that studies the efficient use of limited resources to produce and distribute goods and services in order to satisfy as much as possible the unlimited needs and demands of the society. More simply, economics is the science of choice and how society manages its limited resources. Moreover, it should be emphasized that economics (economic theory) studies only the distribution, exchange and consumption of the economic wealth (food, beverages, clothing, housing, machine tools, computers, services, etc.), the production of which is possible and limited. And the wealth that exists indefinitely: no economic relations are formed in the production and distribution of solar energy, air, and the like. This current book is the second complete updated edition of the challenges of the modern global economy in the context of the coronary crisis, taking into account some of the priority directions of the country's development. Its purpose is to help students and interested readers gain a thorough knowledge of economics and show them how this knowledge can be applied pragmatically (professionally) in professional activities or in everyday life. To achieve this goal, this textbook, which consists of two parts and tests, discusses in simple and clear language issues such as: the essence of economics as a science, reasons for origin, purpose, tasks, usefulness and functions; Basic principles, problems and peculiarities of economics in different economic systems; Needs and demand, the essence of economic resources, types and limitations; Interaction, mobility, interchangeability and efficient use of economic resources. The essence and types of wealth; The essence, types and models of the economic system; The interaction of households and firms in the market of resources and products; Market mechanism and its elements - demand, supply and price; Demand and supply elasticity; Production costs and the ways to reduce them; Forms of the market - perfect and incomplete competition markets and their peculiarities; Markets for Production Factors and factor incomes; The essence of macroeconomics, causes and importance of origin; The essence and calculation of key macroeconomic indicators (gross national product, gross domestic product, net national product, national income, etc.); Macroeconomic stability and instability, unemployment, inflation and anti-inflationary policies; State regulation of the economy and economic policy; Monetary and fiscal policy; Income and standard of living; Economic Growth; The Corona Pandemic as a Defect and Effect of Globalization; National Economic Problems and New Opportunities for Development in the conditions of the Coronary Crisis; The Socio-economic problems of moral obsolescence in digital technologies; Education and creativity are the main solution way to overcome the economic crisis caused by the coronavirus; Positive and negative effects of tourism in Georgia; Formation of the middle class as a contributing factor to the development of tourism in Georgia; Corporate culture in Georgian travel companies, etc. The axiomatic truth is that economics is the union of people in constant interaction. Given that the behavior of the economy reflects the behavior of the people who make up the economy, after clarifying the essence of the economy, we move on to the analysis of the four principles of individual decision-making. Furtermore, the book describes how people make independent decisions. The key to making an individual decision is that people have to choose from alternative options, that the value of any action is measured by the value of what must be given or what must be given up to get something, that the rational, smart people make decisions based on the comparison of the marginal costs and marginal returns (benefits), and that people behave accordingly to stimuli. Afterwards, the need for human interaction is then analyzed and substantiated. If a person is isolated, he will have to take care of his own food, clothes, shoes, his own house and so on. In the case of such a closed economy and universalization of labor, firstly, its productivity will be low and, secondly, it will be able to consume only what it produces. It is clear that human productivity will be higher and more profitable as a result of labor specialization and the opportunity to trade with others. Indeed, trade allows each person to specialize, to engage in the activities that are most successful, be it agriculture, sewing or construction, and to buy more diverse goods and services from others at a relatively lower price. The key to such human interactions is that trade is mutually beneficial; That markets are usually the good means of coordination between people and that the government can improve the results of market functioning if the market reveals weakness or the results of market functioning are not fair. Moroever, it also shows how the economy works as a whole. In particular, it is argued that productivity is a key determinant of living standards, that an increase in the money supply is a major source of inflation, and that one of the main impediments to avoiding inflation is the existence of an alternative between inflation and unemployment in the short term, that the inflation decrease causes the temporary decline in unemployement and vice versa. The Understanding creatively of all above mentioned issues, we think, will help the reader to develop market economy-appropriate thinking and rational economic-commercial-financial behaviors, to be more competitive in the domestic and international labor markets, and thus to ensure both their own prosperity and the functioning of the country's economy. How he/she copes with the tasks, it is up to the individual reader to decide. At the same time, we will receive all the smart useful advices with a sense of gratitude and will take it into account in the further work. We also would like to thank the editor and reviewers of the books. Finally, there are many things changing, so it is very important to realize that the XXI century has come: 1. The century of the new economy; 2. Age of Knowledge; 3. Age of Information and economic activities are changing in term of innovations. 1. Why is the 21st century the century of the new economy? Because for this period the economic resources, especially non-productive, non-recoverable ones (oil, natural gas, coal, etc.) are becoming increasingly limited. According to the World Energy Council, there are currently 43 years of gas and oil reserves left in the world (see “New Commersant 2007 # 2, p. 16). Under such conditions, sustainable growth of real gross domestic product (GDP) and maximum satisfaction of uncertain needs should be achieved not through the use of more land, labor and capital (extensification), but through more efficient use of available resources (intensification) or innovative economy. And economics, as it was said, is the science of finding the ways about the more effective usage of the limited resources. At the same time, with the sustainable growth and development of the economy, the present needs must be met in a way that does not deprive future generations of the opportunity to meet their needs; 2. Why is the 21st century the age of knowledge? Because in a modern economy, it is not land (natural resources), labor and capital that is crucial, but knowledge. Modern production, its factors and products are not time-consuming and capital-intensive, but science-intensive, knowledge-intensive. The good example of this is a Japanese enterprise (firm) where the production process is going on but people are almost invisible, also, the result of such production (Japanese product) is a miniature or a sample of how to get the maximum result at the lowest cost; 3. Why is the 21st century the age of information? Because the efficient functioning of the modern economy, the effective organization of the material and personal factors of production largely depend on the right governance decision. The right governance decision requires prompt and accurate information. Gone are the days when the main means of transport was a sailing ship, the main form of data processing was pencil and paper, and the main means of transmitting information was sending letters through a postman on horseback. By the modern transport infrastructure (highways, railways, ships, regular domestic and international flights, oil and gas pipelines, etc.), the movement of goods, services and labor resoucres has been significantly accelerated, while through the modern means of communication (mobile phone, internet, other) the information is spreading rapidly globally, which seems to have "shrunk" the world and made it a single large country. The Authors of the book: Ushangi Samadashvili, Doctor of Economic Sciences, Associate Professor of Ivane Javakhishvili Tbilisi State University - Introduction, Chapters - 1, 2, 3, 4, 5, 6, 9, 10, 11,12, 15,16, 17.1,18 , Tests, Revaz Shengelia, Doctor of Economics, Professor of Georgian Technical University, Chapters_7, 8, 13. 14, 17.2, 17.4; Zhuzhuna Tsiklauri - Doctor of Economics, Professor of Georgian Technical University - Chapters 13.6, 13.7,17.2, 17.3, 18. We also thank the editor and reviewers of the book.
Book chapters on the topic "Key Productivity Indicators"
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Zulfiu Alili, Merita. "Key Performance Indicators of Public-Owned Enterprises (POEs) in North Macedonia." In CIRIEC Studies Series, 113–24. Liège: CIRIEC, 2021. http://dx.doi.org/10.25518/ciriec.css2northmacedonia.
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Private sector leads the production and distribution process in many countries. However, Public Owned Enterprises (POEs) are also an important element of many developing and developed economies in this context. This analysis examines the main legal organisation forms of public owned enterprises and their financial performance. It also briefly analyses the national legislation and regulation on corruption prevention mechanisms and policy measures and anticorruption practices in public owned enterprises. Almost half of public owned enterprises in North Macedonia are working with losses and have the highest maturity and unpaid liabilities in the last five years. Public owned enterprises can either contribute or obstruct the competitiveness of the economy depending on their efficiency and productivity. This sector needs to be transparent to provide competing enterprises with a fair overview of the fundamental market conditions.
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Stockdale, Elizabeth, Paul Hargreaves, and Anne Bhogal. "Developing soil health indicators for improved soil management on farm." In Advances in measuring soil health, 289–328. Burleigh Dodds Science Publishing, 2021. http://dx.doi.org/10.19103/as.2020.0079.22.
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A range of chemical, physical and biological processes are important for sustained productivity and environmental quality in agricultural systems. Farmers and scientists share a concern with soil health, and this leads to questions for both measurement and management. An essential step is to define the context and the key functions required of a soil at the scale of interest (e.g. farm, drinking water catchment, region). Only then can appropriate indicator measurements be selected. Current soil health frameworks across the world commonly use organic matter (carbon), pH, extractable phosphorus, and various indicators of soil structure/water storage. A framework of interpretation shows whether the measured values are acceptable or whether one or more soil functions are constrained. A number of the soil health frameworks in practical use present the soil health indicators in a scorecard using traffic light coding to direct users towards guidance for improved soil management on-farm.
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Rosiek, Anna, Krzysztof Leksowski, Aleksander Goch, Aleksandra Rosiek-Kryszewska, and Łukasz Leksowski. "Medical Treatment and Difficult Ethical Decisions in Interdisciplinary Hospital Teams." In Healthcare Ethics and Training, 1381–413. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-2237-9.ch066.
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The chapter focuses on organizational culture and ethics, and authors refer to some studies on organizational climate. Authors analyze the relationship between organizational culture and types of performance indicators, which include key concerns of policy makers and the public regarding of hospital behavior. The indicators include resource use per patient (communication process and treatment method, technology, ethical behavior), productivity in resource use (by improving the teamwork and staff education), short-term profitability, patient satisfaction with medical care, and employee satisfaction with improved work culture.
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Rosiek, Anna, Krzysztof Leksowski, Aleksander Goch, Aleksandra Rosiek-Kryszewska, and Łukasz Leksowski. "Medical Treatment and Difficult Ethical Decisions in Interdisciplinary Hospital Teams." In Advances in Medical Education, Research, and Ethics, 121–53. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9658-7.ch006.
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The chapter focuses on organizational culture and ethics, and authors refer to some studies on organizational climate. Authors analyze the relationship between organizational culture and types of performance indicators, which include key concerns of policy makers and the public regarding of hospital behavior. The indicators include resource use per patient (communication process and treatment method, technology, ethical behavior), productivity in resource use (by improving the teamwork and staff education), short-term profitability, patient satisfaction with medical care, and employee satisfaction with improved work culture.
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Popescu, Cristina Raluca Gh. "Sustainable and Responsible Entrepreneurship for Value-Based Cultures, Economies, and Societies." In Sustainable and Responsible Entrepreneurship and Key Drivers of Performance, 33–58. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-7951-0.ch002.
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Entrepreneurship represents the very basis of powerful societies and the essence of robust economies, bringing unique contributions to both sustainable development and economic growth processes. In addition, corporate social responsibility constitutes the key ingredient for all businesses, encouraging competitiveness, ensuring performance, and enabling excellence, while promising a safe and sustainable environment. On one hand, this chapter reviews the theory on sustainable and responsible entrepreneurship as the core of environmental and societal success, and on the other hand, it focuses on the manner in which intangible business assets and intellectual capital yield creativity, innovation, motivation, productivity, and value in challenging times (COVID-19 pandemic). This multidisciplinary study, based on quantitative and qualitative indicators, reports that intellectual capital factor plays a dominant role in constructing new products, rules, and services for the marketplace and highlights the main economic, social, and environmental effects of current business practices.
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Tetteh, Edem G., Ephrem Eyob, and Yao Amewokunu. "Evaluation of Key Metrics for Performance Measurement of a Lean Deployment Effort." In Customer-Oriented Global Supply Chains, 224–35. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-0246-5.ch014.
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To meet customer’s needs for high-quality goods and avoiding risks of product-liability, global firms continually evaluate the performance of their supply chain for optimum design. Lean management is one of the key techniques businesses adopt in redesigning their processes. The technique is a vital strategy to increase productivity and effectiveness with respect to the movement of goods. Multivariate Analysis of Variance (MANOVA) was utilized to evaluate the performance of work cell, shift, worker’s experience, and kaizen event participation level during a lean enterprise deployment effort at a multinational organization. The significance of the effects of these variables were assessed based on various lean supply chain factors such as First In First Out (FIFO), Setup Wheel System (SWS), Standard Operating Procedures (SOP), Clip System(CS), and Key Performances Indicators (KPI). The results support the criticality of metrics and their impact in implementing a lean manufacturing process in a global supply chain environment.
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Imer, S. Tugrul. "The Integrity of the Manufacturing and Innovation Ecosystems With the Scope of University-Industry Collaboration." In University-Industry Collaboration Strategies in the Digital Era, 110–29. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-3901-9.ch006.
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Innovation-based manufacturing remains the key factor in the creation of growth and prosperity. The historical indicators point to the prominent contribution of technology-based manufacturing in boosting productivity. In this context, this chapter argues that successful and sustainable innovation is possible when skilled human resources, universities, R&D facilities, and factories are located in close proximity. This approach is discussed through the impact of the of deindustrialization and reindustrialization trends in the U.S. which began in early 1980s, when neoliberal policies speeded the tendency of relocating many manufacturing businesses overseas mainly to benefit from low cost labor. However, beginning from the past decade, the U.S. Government policies have been prominently shifting towards reshoring some of the manufacturing facilities to the U.S. soil. Consistently, the historical facts show that a stronger innovation capacity is linked with an intimately associated and efficiently functioning university-industry collaboration system..
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Bronzetti, Giovanni, Maria Assunta Baldini, and Graziella Sicoli. "The Measurement of Human Capital in Family Firms." In Handbook of Research on Human Resources Strategies for the New Millennial Workforce, 371–92. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-0948-6.ch019.
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Intangibles are the key elements underpinning the competitiveness of enterprises. Among them a decisive role is certainly represented by the skills, knowledge, skills and experience possessed by members within organizations, as fundamental drivers thanks to which delineate identity and strategic objectives. Intangible assets became the determinants and foremost sources of company success (Drucker, 1993). The literature on human capital proposed that firms require to recruit, nurture and retain talents so that the knowledge base can be extended, which has the capacity to improve an organization's overall productivity (Boxall, 2003; Lin & Wang, 2005, Lim et al., 2010; Mehralian et al., 2013). The management of human capital as an important component of intangible assets often creates and sustains an organization's wealth and competitive advantage (Lim et al., 2010). The main aim of this paper is to define a list of indicators that can be to measure human capital intangibles identified in family firms.
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Poças Rascão, José. "Information System for Logistics and Distribution Management." In Handbook of Research on Information Management for Effective Logistics and Supply Chains, 374–414. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-0973-8.ch021.
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This article aims to design an Information System for Logistics and Distribution Management, albeit an incomplete one. It seeks to define the key performance indicators (financial, time, productivity and quality of services) as an innovative approach to information management, stemming from the understanding of the physical, financial and information flows related to the Logistics and Distribution activities in which the organizations operate, whether they are carried out in the for-profit or nonprofit sector. In this sense, some conceptual clarifications become necessary and are presented in this chapter. The term information unit / business unit, although widespread in management literature, is not defined by consensus. Guinchat and Menou (1994, p.337) use the term to refer to sectors of businesses whose mission is “to identify, as accurately as possible, information that may be useful to decision-makers (top, coordination and operational) in support decision-making.” Logistics and Distribution cannot manage without information on applications / products by and for customers, and their relationship with information management, in Information Science. The structure of the article summarizes existing academic work, seeking to generate new knowledge. It presents information to support decision-making in an integrated and independent way of support-technology.
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Kitchin, Rob. "Management Through Metrics." In Data Lives, 143–52. Policy Press, 2021. http://dx.doi.org/10.1332/policypress/9781529215144.003.0018.
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This chapter studies how public and private sector organizations are increasingly using key performance indicators (KPIs) and technocratic procedures to manage work and workers and its consequences. Since the 1980s and the introduction of new public management (NPM) — an approach to running public sector institutions in a more business-like way — various kinds of assessment have been introduced to measure and track performance. Usually, these measures are institutionalized through formalized assessment schemes designed to improve efficiency, productivity, and quality. An entire bureaucracy has developed to oversee this datafication, and the management of institutions has transformed to become more instrumental and technocratic, guided by metrics. Decisions concerning individual promotion, departmental staffing and budgets, and strategic investments are informed by KPIs and rankings. In places like the UK and Australia, management through metrics has become deeply ingrained into the working lives of academics and the management of institutions. While Ireland has managed to avoid the worst excesses of management through metrics, it has not been totally immune. KPIs are now a part of the management regime and are used to guide decision-making, but they are used alongside other forms of information rather than narrowly determining outcomes.
Conference papers on the topic "Key Productivity Indicators"
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Stundziene, Alina. "Key Indicators for Improving the Resource Productivity in the Baltic States." In BE-ci 2016 International Conference on Business and Economics. Cognitive-crcs, 2016. http://dx.doi.org/10.15405/epsbs.2016.11.02.31.
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Brundage, Michael P., K. C. Morris, Thurston Sexton, Sascha Moccozet, and Michael Hoffman. "Developing Maintenance Key Performance Indicators From Maintenance Work Order Data." In ASME 2018 13th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/msec2018-6492.
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Maintenance management for manufacturing is a crucial activity for improving productivity within a facility. Within this process, maintenance work orders (MWOs) are used when tracking and solving any maintenance–related issue. The MWOs often capture the problem, the solution, at what machine the problem occurred, who solved the problem, when the problem occurred, and other information. These MWOs are manually written by maintenance technicians, entered into a database, or recorded directly into maintenance management software. Technicians often describe or record information informally — or do not record it at all — leading to inconsistencies and/or inaccuracies in the data. This paper outlines maintenance key performance indicators (KPIs), developed using MWOs, that show why consistent and accurate data collection is important for maintenance decision making. The maintenance data, or “elements,” and their corresponding KPIs are derived from MWOs from real manufacturers (large manufacturers and small and medium enterprises). While all elements or KPIs are not recorded by every manufacturer, the guideline provided here outlines the elements necessary to calculate specific KPIs. These examples are developed to aid in common maintenance decisions.
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Karyakin, A. L., and P. A. Osipov. "Increased Productivity with Performance Monitoring of the Key Technological Indicators for Power Shovels and Dragline by Means of Electric Drive." In 30th International Symposium on Automation and Robotics in Construction and Mining; Held in conjunction with the 23rd World Mining Congress. International Association for Automation and Robotics in Construction (IAARC), 2013. http://dx.doi.org/10.22260/isarc2013/0101.
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KOCUR-BERA, Katarzyna. "MULTIFUNCTIONAL RURAL DEVELOPMENT – A COMPARATIVE ANALYSIS OF MUNICIPALITIES ADJACENT TO THE CITY OF OLSZTYN." In RURAL DEVELOPMENT. Aleksandras Stulginskis University, 2018. http://dx.doi.org/10.15544/rd.2017.208.
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Rural areas have multiple functions. Four key functions can be identified in a synthetic approach: economic, environmental, social and cultural. Multidirectional rural development is strongly influenced by spatial attributes, demographics, environmental factors, infrastructure and capital. Multidirectional development is closely associated with the multiple functions of rural areas. In general, multifunctional rural development involves rural activation and rural business diversification which enables members of the rural community to derive incomes from non-farming activities. The growth potential of rural municipalities is an important determinant of multifunctional development. The aim of this study was to analyze the level of socioeconomic development in rural municipalities, which is an indicator of their multifunctional development. The analysis involved rural municipalities adjacent to the city of Olsztyn. These municipalities are bedroom communities whose residents commute to work in the urban center. The study analyzed 15 indicators describing the four key areas of multifunctional development: environmental, social, economic and infrastructural. Data for 2013-2015 were acquired from the Central Statistical Office and statistical tables of the agricultural productivity index. The results indicate that the municipality of Purda (with relatively poor soils) meets the highest number of criteria and the municipality of Dywity (with relatively high-quality soils) meets the lowest number of criteria for multifunctional development.
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Salahshoor, Shadi. "Data-Driven Characterization of Shale Reservoirs Towards Facilitation of Production Performance Evaluation." In SPE Western Regional Meeting. SPE, 2021. http://dx.doi.org/10.2118/200835-ms.
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Abstract Leveraging publicly available data is a crucial stepfor decision making around investing in the development of any new unconventional asset.Published reports of production performance along with accurate petrophysical and geological characterization of the areashelp operators to evaluate the economics and risk profiles of the new opportunities. A data-driven workflow can facilitate this process and make it less biased by enabling the agnostic analysis of the data as the first step. In this work, several machine learning algorithms are briefly explained and compared in terms of their application in the development of a production evaluation tool for a targetreservoir. Random forest, selected after evaluating several models, is deployed as a predictive model thatincorporates geological characterization and petrophysical data along with production metricsinto the production performance assessment workflow. Considering the influence of the completion design parameters on the well production performance, this workflow also facilitates evaluation of several completion strategies toimprove decision making around the best-performing completion size. Data used in this study include petrophysical parameters collected from publicly available core data, completion and production metrics, and the geological characteristics of theNiobrara formation in the Powder River Basin. Historical periodic production data are used as indicators of the productivity in a certain area in the data-driven model. This model, after training and evaluation, is deployed to predict the productivity of non-producing regions within the area of interest to help with selecting the most prolific sections for drilling the future wells. Tornado plots are provided to demonstrate the key performance driversin each focused area. A supervised fuzzy clustering model is also utilized to automate the rock quality analyses for identifying the "sweet spots" in a reservoir. The output of this model is a sweet-spot map that is generated through evaluating multiple reservoir rock properties spatially. This map assists with combining all different reservoir rock properties into a single exhibition that indicates the average "reservoir quality"of the formation in different areas. Niobrara shale is used as a case study in this work to demonstrate how the proposed workflow is applied on a selected reservoir formation whit enough historical production data available.
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Chen, Qinglian, Bitao Yao, and Duc Truong Pham. "Sequence-Dependent Robotic Disassembly Line Balancing Problem Considering Disassembly Path." In ASME 2020 15th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/msec2020-8268.
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Abstract For the realization of environmental protection and resource conservation, remanufacturing is of great significance. Disassembly is a key step in remanufacturing, the disassembly line system is the main scenario for product disassembly, usually consisting of multiple workstations, and has prolific productivity. The application of the robots in the disassembly line will eliminate various problems caused by manual disassembly. Moreover, the disassembly line balancing problem (DLBP) is of great importance for environmental remanufacturing. In the past, disassembly work was usually done manually with high cost and relatively low efficiency. Therefore, more and more researches are focusing on the automatic DLBP due to its high efficiency. This research solves the sequence-dependent robotic disassembly line balancing problem (SDRDLBP) with multiple objectives. It considers the sequence-dependent time increments and requires the generated feasible disassembly sequence to be assigned to ordered disassembly workstations according to the specific robotic workstation assignment method. In robotic DLBP, due to the special characteristics of robotic disassembly, we need to consider the moving time of the robots’ disassembly path during the disassembly process. This is also the first time to consider sequence-dependent time increments while considering the disassembly path of the robots. Then with the help of crossover and mutation operators, multi-objective evolutionary algorithms (MOEAs) are proposed to solve SDRDLBP. Based on the gear pump model, the performance of the used algorithm under different cycle times is analyzed and compared with another two algorithms. The average values of the HV and IGD indicators have been calculated, respectively. The results show the NSGA-II algorithm presents outstanding performance among the three MOEAs, and hence demonstrate the superiority of the NSGA-II algorithm.
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Nejad, Amir M., Stanislav Sheludko, Robert F. Shelley, Trey Hodgson, and Riley McFall. "A Case History: Evaluating Well Completions in the Eagle Ford Shale Using a Data-Driven Approach." In SPE Hydraulic Fracturing Technology Conference. SPE, 2015. http://dx.doi.org/10.2118/spe-173336-ms.
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AbstractUnconventional shale resources are key hydrocarbon sources, gaining importance and popularity as hydrocarbon reservoirs both in the United States and internationally. Horizontal wellbores and multiple transverse hydraulic fracturing are instrumental factors for economical production from shale assets. Hydraulic fracturing typically represents a major component of total well completion costs, and many efforts have been made to study and investigate different strategies to improve well production and reduce costs. The focus of this paper is completion effectiveness evaluation in different parts of the Eagle Ford Shale Formation, and our objective is to identify appropriate completion strategies in the field.A data-driven neural network model is trained on the database comprised of multiple operators' well data. In this model, drilling and mud data are used as indicators for geology and reservoir-related parameters such as pressure, fluid saturation and permeability. Additionally, completion- and fracture-related parameters are also used as model inputs. Because wells are pressure managed differently, normalized oil and gas production is used as a model output. Thousands of neural networks are trained using genetic algorithm in order to fully evaluate hidden correlations within the database. This results in selection of a neural network that is able to understand reservoir, completion and frac differences between wells and identify how to improve future completion/stimulation designs.The final neural network model is successfully developed and tested on two separate data sets located in different parts of the Eagle Ford Shale oil window. Further, an additional test data set comprised of eight wells from a third field location is used to validate the predictive usefulness of the data-driven model. Under-producing wells were also identified by the model and new fracture designs were recommended to improve well productivity.This paper will be useful for understanding the effects of completion and fracture treatment designs on well productivity in the Eagle Ford. This information will help operators select more effective treatment designs, which can reduce operational costs associated with completion/fracturing and can improve oil and gas production.
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Kangru, Tavo, Kashif Mahmood, Tauno Otto, Madis Moor, and Jüri Riives. "Knowledge-Driven Based Performance Analysis of Robotic Manufacturing Cell for Design Improvement." In ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-23541.
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Abstract Manufacturing companies must ensure high productivity and low production cost in rapidly changing market conditions. At the same time products and services are evolving permanently. In order to cope with those circumstances, manufacturers should apply the principles of smart manufacturing together with continuous processes improvement. Smart manufacturing is a concept where production is no longer highly labor-intensive and based only on flexible manufacturing systems, but production as a whole process should be monitored and controlled with sophisticated information technology, integrated on all stages of the product life cycle. Process improvements in Smart Manufacturing are heavily reliance on decisions, which can be achieved by using modeling and simulation of systems with different analyzing tools based on Big Data processing and Artificial Intelligence (AI) technologies. This study was performed to automate an estimation process and improve the accuracy for production cell’s performance evaluation. Although there have been researches performed in the same field, the substantial estimation process outcome and accuracy still need to be elaborated further. In this article a robot integrated production cell simulation framework is developed. A developed system is used to simulate production cell parametric models in the real-life situations. A set of rules and constraints are created and inserted into the simulation model. Data for the constraints were acquired by investigating industries’ best production cells performance parameters. Information was gathered in four main fields: company profile and strategy, cell layout and equipment, manufactured products process data and shortcomings of goal achievements or improvement necessary to perform. From those parametric case model, a 3D virtual manufacturing simulation model is built and simulated for achieving accurate results. The integration of manufacturing data into decision making process through advanced prescriptive analytics models is a one of the future tasks of this study. The integration makes it possible to use “best practice” data and obtained Key Performance Indicators (KPIs) results to find the optimal solutions in real manufacturing conditions. The objective is to find the best solution of robot integrated cell for a certain industry using AI enabled simulation model. It also helps to improve situation assessment and deliberated decision-making mechanism.
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Mondal, Somnath, Ashan Garusinghe, Sebastian Ziman, Muhammed Abdul-Hameed, Rakesh Paleja, Matthew Jones, Jan Limbeck, et al. "Efficiency and Effectiveness - A Fine Balance: An Integrated System to Improve Decisions in Real-Time Hydraulic Fracturing Operations." In SPE Hydraulic Fracturing Technology Conference and Exhibition. SPE, 2022. http://dx.doi.org/10.2118/209127-ms.
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Abstract Hydraulic fracturing is a key driver of well productivity and field development planning, in addition to being the most significant portion of capex in shales. Recent breakthroughs in connectivity and digital technologies have enabled the monitoring and analyses of frac operations in real-time. However, most of the digitalization effort to date has been focused on increasing operational efficiency to reduce cost. Without an equal consideration for creating effective fracture geometries, this may lead to poor resource recovery and leave significant value behind. In this paper, we - 1) demonstrate the need to balance between optimizing fracture efficiency and effectiveness; 2) present an integrated system for frac optimization using real-time, historical data along with organizational knowledge; and 3) discuss the challenges of setting up such a system and key considerations, along with examples of large, untapped potential that can be unlocked with data science to deliver real value. Currently, several service providers exist to stream frac data with interactive analytics dashboards. While they offer some customizability, most do not provide a true frac optimization platform that goes beyond frac monitoring and analytics geared towards efficiency and cost indicators. We are still dependent on an individual operator's experience and rules of thumb to make job decisions during a frac stage. In this paper, a real-time optimization workflow is presented that uses advanced data science and statistical techniques to interpret and predict time-series treatment data, integrate historical and contextual information, and honor basin-specific knowledge that has been gathered and tested over the years. Examples are presented from diagnostic pads that highlight the need for balancing stimulation effectiveness with efficiency. We demonstrate a platform to host and execute an ensemble of models and visualizations that communicate actionable insights to an operator within minutes of identifying an event, gather feedback, and learn. Results from field testing show that our system accelerates the learning curve, enables consistent decision making by operators, and can generate significant cost savings. Finally, we share learnings from our digitalization journey. Completion and stimulation expenses account for approximately half of an unconventional well cost. Automated decision making for real-time fracture treatment is the holy grail of digital completions in shales. However, a blind pursuit of efficiency may lead to sub-par fracture treatments and significant value erosion for shale assets. We present an integrated framework that connects real-time data and organizational knowledge to guide an operator to pump the best frac stage while reacting to formation response within a set of constraints. To the best of our knowledge, this is the first paper to describe the general architecture and demonstrate the viability of such a system that relies only on standard wellhead measurements during fracturing.
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Avila, Juan Carlos, and Justino Felix Capululo. "Correlation Between Completion Quality and Productivity Degradation Narrows Down Uncertainty in Production Forecasts." In Offshore Technology Conference. OTC, 2022. http://dx.doi.org/10.4043/32015-ms.
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Abstract Productivity index (PI) degradation is a critical issue that negatively impacts hydrocarbon recovery. This problem is very common in deepwater environments such as Gulf of Mexico (GOM). In recent years, several publications have addressed this issue proposing integrated workflows to assess and mitigate this problem and providing interesting insights into the causes of this phenomenon. Our organization commissioned a study (Knobles et al. 2017) to understand the reasons for the high productivity declines observed across our assets in GOM and identify lessons learned and best practices to reduce the severity of the PI degradation in cased-hole-frac-pack (CHFP) completions in high-permeability reservoirs (50-1000 mD), which are the most common in our operations. These findings have contributed to improve our CHFP performance. This performance has been assessed based on a completion scorecard that grades and weights the key design and execution parameters of the CHFP completion and yields a score (0 to 100) for the completion execution and productivity. Knobles et al. established a correlation between the productivity score in the completion scorecard and a qualitative ranking of the well productivity performance, namely productivity tiers. The wells in scope were categorized in four groups, tier 1, tier 2, tier 3, and tier 4. Tier 1 is the highest performance level, i.e., low initial skin and low productivity degradation. Later, the completion scorecard was reviewed by a group of completion subject-matter experts (SME) to improve the correlation between the productivity score and the productivity tiers. The updated scorecard enhanced this relationship making it suitable as an indicator of long-term productivity. However, the use of this correlation in production forecasting is limited because of its categorical nature. The objective of this work is to quantify the relationship between the completion scorecard and the productivity performance and use the results to narrow down the productivity degradation uncertainty range in production forecasts. We use data science concepts and tools to analyze our well productivity database, Integral Well Productivity Tracker (IWPT), and develop a numeric correlation between the actual well productivity data observed in the field and the completion scorecard results from the post-job evaluations. The process includes IWPT data wrangling, modeling, and visualization. We performed regression analyses on the normalized productivity index and cumulative liquid production for approximately 120 wells in the IWPT dataset to calculate PI degradation rate for each well and combine them with the completion scorecard results. The results validate the conclusion from Knobles et al.'s work, i.e., a correlation exits between the productivity score from the completion scorecard and the productivity performance. The new, numerical relationship allows us to consider the improvements in completion quality. This quantitative correlation can inform the definition of the productivity-degradation-uncertainty ranges in the production forecast during planning and after the completion job when the completion scorecard results are available. Narrowing down the uncertainty in productivity degradation significantly impacts the estimated-ultimate recovery (EUR) of any GOM deepwater project.
Reports on the topic "Key Productivity Indicators"
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Banerjee, Onil, Martin Cicowiez, Ana Rios, and Cicero De Lima. Climate Change Impacts on Agriculture in Latin America and the Caribbean: An Application of the Integrated Economic-Environmental Modeling (IEEM) Platform. Inter-American Development Bank, November 2021. http://dx.doi.org/10.18235/0003794.
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In this paper, we assess the economy-wide impact of Climate Change (CC) on agriculture and food security in 20 Latin American and the Caribbean (LAC) countries. Specifically, we focus on the following three channels through which CC may affect agricultural and non-agricultural production: (i) agricultural yields; (ii) labor productivity in agriculture, and; (iii) economy-wide labor productivity. We implement the analysis using the Integrated Economic-Environmental Model (IEEM) and databases for 20 LAC available through the OPEN IEEM Platform. Our analysis identifies those countries most affected according to key indicators including Gross Domestic Product (GDP), international commerce, sectoral output, poverty, and emissions. Most countries experience negative impacts on GDP, with the exception of the major soybean producing countries, namely, Brazil, Argentina and Uruguay. We find that CC-induced crop productivity and labor productivity changes affect countries differently. The combined impact, however, indicates that Belize, Nicaragua, Guatemala and Paraguay would fare the worst. Early identification of these hardest hit countries can enable policy makers pre-empting these effects and beginning the design of adaptation strategies early on. In terms of greenhouse gas emissions, only Argentina, Chile and Uruguay would experience small increases in emissions.