Дисертації з теми "Total production cost optimisation"

L'industrie de la production actuelle est caractérisée par des progrès significatifs : une augmentation massive de la haute technologie, l'émergence de clients exigeants, des marchés compétitifs, une qualité de produit variée et des demandes aléatoires ont exigé la collaboration des aspects interdépendants de la production. La production, la maintenance et la qualité sont les aspects les plus critiques du système industriel. Nous nous intéressons à l'optimisation de la maintenance qui joue un rôle essentiel dans la satisfaction du client, la durabilité et le développement des entreprises. Notre étude est centrée sur le développement de la production et de la maintenance intégrées dans une carte de contrôle de la politique de qualité. Nous proposons de nouvelles stratégies de maintenance intégrée avec une analyse approfondie des améliorations continues de la fiabilité du processus de production et traitées sous les contraintes des exigences du client (Service, qualité et coût). L'intégration et la coordination optimale de ces facteurs de production n'est pas facile et représente un défi pour les entreprises industrielles, et sont plus difficiles avec les causes multi-assignables de la variation du processus de production. Pour répondre à ce problème, ce travail de recherche a utilisé l'outil carte de contrôle en combinaison avec les principes de l'AFNOR connus sous le nom de Règle des sept comme impliqués dans la gestion de la qualité. Pour surveiller, analyser et diriger les actions de maintenance appropriées pour l'amélioration continue de la fiabilité du système le long des différents scénarios de processus multiples comme niveaux de décision. Nous utilisons les interactions entre le processus de production et la qualité du produit pour des stratégies de maintenance qui réduisent la défaillance du système de production en améliorant la fiabilité du processus et en réduisant les produits non conformes. L'étude a porté de manière significative sur la qualité, les outils de qualité et leurs applications dans le contrôle de la production et de la maintenance. La technique que nous avons utilisée pour optimiser la maintenance et le contrôle de la qualité d'un système de production intégré est un outil de carte de contrôle basé sur la mesure et l'analyse statistique des paramètres de qualité. Nous modélisons différents problèmes de production et développons une politique de contrôle pour des systèmes de production à défaillance aléatoire qui doivent satisfaire les exigences des clients de manière dynamique tout au long de l'horizon de production fini. Nous avons introduit un modèle mathématique pour minimiser les coûts totaux de production, d'inventaire, de maintenance et de contrôle de la qualité. L'optimisation de la stratégie de maintenance a été intégrée dans un outil d'information sur les cartes de contrôle. Sur la base de la variation du taux de production et de son impact sur la dégradation de la machine, le nombre de maintenance, les temps et les intervalles nécessaires à une prise de décision prudente sont déterminés par l'algorithme développé. Dans ce contexte, cette recherche présente la dérivation pour différents cas de toutes les probabilités pour le processus d'être dans ou hors de contrôle, les durées moyennes d'exécution, et les durées de cycle de restauration. Sur la base du facteur de dégradation, de nouvelles équations de taux de défaillance sont formulées, puis le taux de défaillance moyen pour chaque cas, nous avons formulé différents modèles d'optimisation des coûts de maintenance. L'approche proposée est utile pour le calcul précis et la minimisation du coût total de maintenance. Elle optimise le coût total de production en considérant tous les états possibles du processus de production dus à des causes multiples. Notre travail contribue à l'émergence de techniques de gestion de la qualité et d'amélioration des performances qui contribueront au développement des entreprises de production
The current production industry is characterise by significant progress: a massive increase in high technology, the emergence of exigent customers, competitive markets, varied product quality, and random demands required the collaborations of the inter-related aspects of production. The production, maintenance, and quality are the most critical aspects of the industrial system. We are interested in optimising maintenance that plays a critical role in customer satisfaction, sustainability, and the development of companies. Our study is centred on developing production and maintenance integrated into a control chart of quality policy. We propose new integrated maintenance strategies with an in-depth analysis of the continuous production process reliability improvements and treated under customer requirements (Service, quality, and cost) constraints. The integration and optimal coordination of these factors of production is not easy and represent a challenge for industrial companies, and are more challenging with multi-assignable causes of production process variation. To address this problem, this research work employed the use of a control chart tool in combination with the AFNOR principles known as Rule of seven as involved in quality management. To monitor, analyses and direct appropriate maintenance actions for continuous system reliability improvements along the different multiple process scenarios as decision levels. We use the interactions between the production process and product quality for strategies of maintenance which reduce the failure of the production system by improving process reliability and reducing the no conformal products. The study Significantly focused on quality, quality tools, and their applications in production and maintenance control. The technique we used to optimise the maintenance and quality control of an integrated production system is a control chart tool based on statistical measurement and analysis of quality parameters. We model different production problems and develop a control policy for randomly failing production systems that must satisfy customer requirements dynamically throughout the finite production horizon. We introduced a mathematical model to minimise the total costs of production, inventory, maintenance, and quality control. The optimisation of the maintenance strategy was integrated into a control chart tool information. Based on the production rate variation and its impact on machine degradation the number of maintenance, times, and intervals needed for prudent decision-making is determined by the developed algorithm. In this context, this research presents the derivation for different cases of all the probabilities for the process to be in or out of control, the average run lengths, and the restoration cycle durations. Based on the degradation factor, new failure rate equations are formulated, and then the average failure rate for each case, we formulated different maintenance cost optimisation models. The proposed approach is useful for precise calculation and minimisation of the total maintenance cost. Which optimises total production cost considering all possible production process statuses due to multiple causes. Our work contributes to the emergence of quality management and performance improvement techniques that will contribute to the development of production companies

In this thesis, the effect of pitch based optimisation was explored for a 80 turbine wind farm. Using a modified Jensen wake model and the Particle Swarm Optimisation (PSO) model, a pitch optimisation strategy was created for the dominant turbulence and atmospheric condition for the wind farm. As the wake model was based on the FLORIS model developed by P.M.O Gebraad et. al., the wake and power model was compared with the FLORIS model and a -0.090% difference was found. To determine the dynamic predictive capability of the wake model, measurement values across a 10 minute period for a 19 wind turbine array were used and the wake model under predicted the power production by 17.55%. Despite its poor dynamic predictive capability, the wake model was shown to accurately match the AEP production of the wind farm when compared to a CFD simulation done in FarmFlow and only gave a 3.10% over-prediction. When the optimisation model was applied with 150 iterations and particles, the AEP production of the wind farm increased by 0.1052%, proving that the pitch optimisation method works for the examined wind farm. When the iterations and particles used for the optimisation was increased to 250, the power improvement between optimised results improved by 0.1144% at a 222.5% increase in computational time, suggesting that the solution has yet to fully converge. While the solutions did not fully converge, they converged sufficiently and an increase in iterations gave diminishing results. From the results, the pitch optimisation model was found to give a significant increase in power production, especially in wake intensive wind directions. However, the dynamic predictive capabilities will have be improved upon before the control strategy can be applied to an operational wind farm.

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2019, In conjunction with the Leaders for Global Operations Program at MIT
Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2019, In conjunction with the Leaders for Global Operations Program at MIT
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 76-77).
In an ideal production system, supply exactly meets demand. Instantaneous, correct quantities arrive exactly at the right location when needed. However, real-world production systems often have variability- a change in the quantity demanded, a broken part, a shipping delay for a snow storm. The variability can be random, so companies are left with a dilemma: too little inventory buffer and a shortage may occur; too much inventory and capital is unnecessarily tied up in inventory sitting on the shelves. Using research conducted at the Boeing 737 program as a case study, this thesis proposes the application of a multi-step approach to optimize the total cost of the production system, balancing holding cost (inventory) with the disruption cost of a shortage. The initial pilot shows that small increases in inventory can have an order of magnitude of cost avoidance. The methodology includes system observation, qualitative interviews with Boeing employees, quantitative data gathering and analysis, proposed changes, and measured results. First, the historical supply and demand variability of the system is identified. Second, the cost of a shortage is estimated for the system. Next, an analytical approach to set safety stock levels is applied to balance the cost of inventory held with the cost of a shortage. By reducing the variability in the system, inventory levels can be reduced while maintaining the service levels. This process is then repeated at regular intervals to optimize the total cost of the system, balancing inventory holding cost and the disruption cost of a shortage.
by Jacob Philip Pellegrini.
M.B.A.
S.M.
M.B.A. Massachusetts Institute of Technology, Sloan School of Management
S.M. Massachusetts Institute of Technology, Department of Mechanical Engineering

Manufacturing enterprises nowadays face the challenge of increasing energy prices and requirements to reduce their emissions. Most reported work on reducing manufacturing energy consumption focuses on the need to improve the efficiency of resources (machines). The potential for energy reducing at the system-level has been largely ignored. At this level, operational research methods can be employed as the energy saving approach. The advantage is clearly that the scheduling and planning approach can be applied across existing legacy systems and does not require a large investment. For the emission reduction purpose, some electricity usage control policies and tariffs (EPTs) have been promulgated by many governments. The Rolling Blackout policy in China is one of the typical EPTs, which means the government electricity will be cut off several days in every week for a specific manufacturing enterprise. The application of the Rolling Blackout policy results in increasing the manufacturing enterprises’ costs since they choose to start to use much more expensive private electricity to maintain their production. Therefore, this thesis develops operational research methods for the minimisation of electricity consumption and the electricity cost of job shop type of manufacturing systems. The job shop is selected as the research environment for the following reasons. From the academic perspective, energy consumption and energy cost reduction have not been well investigated in the multi-objective scheduling approaches to a typical job shop type of manufacturing system. Most of the current energy-conscious scheduling research is focused on single machine, parallel machine and flow shop environments. From the practical perspective, job shops are widely used in the manufacturing industry, especially in the small and medium enterprises (SMEs). Thus, the innovative electricity-conscious scheduling techniques delivered in this research can provide for plant managers a new way to achieve cost reduction. In this thesis, mathematical models are proposed for two multi-objective job shop scheduling optimisation problems. One of the problems is a bi-objective problem with one objective to minimise the total electricity consumption and the other to minimise the total weighted tardiness (the ECT problem). The other problem is a tri-objective problem which considers reducing total electricity consumption, total electricity cost and total weighted tardiness in a job shop when the Rolling Blackout policy is applied (the EC2T problem). Meta-heuristics are developed to approximate the Pareto front for ECT job shop scheduling problem including NSGA-II and a new Multi-objective Genetic Algorithm (GAEJP) based on the NSGA-II. A new heuristic is proposed to adjust scheduling plans when the Rolling Blackout policy is applied, and to help to understand how the policy will influence the performance of existing scheduling plans. NSGA-II is applied to solve the EC2T problem. Six scenarios have been proposed to prove the effectiveness of the aforementioned algorithms. The performance of all the aforementioned heuristics have been tested on Fisher and Thompson 10×10, Lawrence 15×10, 20×10 and 15×15 job shop scenarios which were extended to incorporate electrical consumption profiles for the machine tools. Based on the tests and comparison experiments, it has been found that by applying NSGA-II, the total non-processing electricity consumption in a job shop can decrease considerably at the expense of the schedules’ performance on the total weighted tardiness objective when there are tight due dates for jobs. When the due dates become less tight, the sacrifice of the total weighted tardiness becomes much smaller. By comparing the Pareto fronts obtained by GAEJP and by NSGA-II, it can be observed that GAEJP is more effective in reducing the total non-processing electricity consumption than NSGA-II, while not necessarily sacrificing its performance on total weighted tardiness. Thus, the superiority of the GAEJP in solving the ECT problem has been demonstrated. The scheduling plan adjustment heuristic has been proved to be effective in reducing the total weighted tardiness when the Rolling Blackout policy is applied. Finally, NSGA-II is proved to be effective to generate compromised scheduling plans for using the private electricity. This can help to realise the trade-off between the total weighted tardiness and the total electricity cost. Finally, the effectiveness of GAJEP in reducing the total non-processing electricity consumption has been validated in a real-world job shop case.

Le contexte actuel impose aux entreprises des délais de plus en plus serrés, alors que la demande est de plus en plus irrégulière. Dans cet environnement incertain, notre travail concerne la mise en œuvre des méthodologies coopératives pour résoudre les problèmes des job-shops flexibles avec des demandes prévisionnelles. Il s'articule autour de deux parties principales. La première consiste à trouver un ordonnancement pour les demandes fermes. La deuxième consiste à insérer les demandes prévisionnelles dans les solutions initiales en optimisant les critères considérés, en utilisant des méthodes d'insertion (statique et dynamique). Pour tester l'efficacité des solutions, on à déterminer deux approches de calcul des bornes inférieures pour les critères (bornes des demandes fermes et des prévisionnelles). Une méthode de résolution pour les problèmes multicritères en affectant les poids de préférence des critères dynamiquement. Enfin, nous concluons par des d'exemples d'applications
In this work, we consider the flexible job-shop scheduling problem with uncertain demands and we develop a new cooperative methodology to solve it. It is organized in two main parts. The first one consists in finding a scheduling for the firm demands. The second one consists in developing methods allowing of insertion the predicted demands in the solutions found initially with insertion methods (static method and dynamic method) while optimizing the considered criteria. To test the effectiveness of these solutions, we determine an approach based on the calculation of the lower bounds for the criteria, which calculation on the firm demands and on the estimated ones. A method of resolution for multicriterion problems is proposed to help the decision maker when it cannot give a particular preference to the criteria. Moreover, we validate these methods on a series of example. Finaly, we conclude this memory by listing some advantages of our methods

Background: China is one of the most popular countries to relocate and outsource production units to. This country has a big advantage when it comes to the manual working cost which is very low. This difference between Sweden and China is huge; the cost of the manual working force is less than one twentieth of the Swedish.

Problem: Massive global relocation of production units can affect some countries in a negative way. One of the most important foundations in the society is that there is a high level of employment and this also contributes for economic growth. This is in terms of both tax incomes for the public society as well as self-esteem for the people.

Purpose: The purpose with this thesis is to examine the differences in total production costs, including allocation of overhead costs for product development and production in Sweden vs. China at a company, in this thesis referred to as Manufacturer AB.

Method: Case study approach with in-depth interviews, phone calls and e-mail follow up. In total 9 respondents consisting of managers in leading positions at Manufacturer AB in Sweden.

Conclusion: The manufacturing cost in the Chinese production unit is about 40-60 per cent compared to the Swedish unit. In the current situation the overhead allocation is 4 % overhead of MC at the Chinese production unit and 133 % at the Swedish unit. The total production costs are not reflected in a correct way per unit. To do a more true allocation, the overhead costs in the Company Group must be identified and allocated in the right proportions on their respective production unit.

By creating an average- and in next step an estimated allocation model we succeeded to do a more justified allocation of the overhead costs on the production units in Sweden and China. This model should be relative simple to implement on product- or unit level and gives a more correct allocation than the current.

However, it is the decision of Manufacturer AB to allocate their overhead as they like, but the estimated allocation model gives a base for strategic decisions on production unit level, referring to; where to locate the production units to reach competitive advantage.

Bakgrund: Kina är ett av de mest populära länderna att utlokalisera och outsourca produktionsenheter till. Detta land har en stor fördel när det gäller kostnaden för manuellt arbete, som är väldigt låg. Skillnaden mellan Sverige och Kina är enorm; kostnaden för den manuella arbetstiden är ca en tjugondel av den svenska.

Problem: Massiva globala omflyttningar av produktionsanläggningar kan påverka vissa länder negativt. En av de viktiga grundpelarna i samhället är att det finns en hög sysselsättningsgrad som bidrar till ekonomisk tillväxt. Detta gäller såväl skatteintäkter till staten som självkänsla hos folket.

Syfte: Syftet med den här uppsatsen är att undersöka skillnaderna i den totala produktionskostnaden, inkluderat fördelning av overheadkostnader för produktutveckling och produktion i Sverige jämfört med Kina vid ett företag som i denna uppsats refereras till Manufacturer AB.

Metod: Fallstudie är gjord med hjälp av personliga djupintervjuer, uppföljande telefonsamtal och elektronisk post. Totalt deltog 9 respondenter bestående av tjänstemän i ledande positioner på Manufacturer AB i sverige.

Slutsats: Tillverkningskostnaden i den Kinesiska produktionsenheten är ungefär 40-60 procent jämfört med motsvarande enhet i Sverige. I nuläget är overheadpålägget 4% på produktionsenheten i Kina och 133% på enheten i Sverige. Den totala produktionskostnaden speglas inte på ett rättvist sätt per produktionsenhet. För att göra en mer rättvis fördelning så måste koncernens totala overheadkostnad identifieras och mätas och sedan allokeras i de rätta proportionerna på respektive produktionsenhet.

Genom att skapa en genomsnittlig och i nästa steg en uppskattad fördelningsmodell lyckades vi att göra en mer rättvis fördelning av overheadkostnaderna på produktionsenheterna i Sverige och Kina. Denna modell borde vara ganska enkel att implementera på produkt- eller enhetsnivå och ger en mer korrekt fördelning än den nuvarande.

Hursomhelst, är det upp till Manufacturer AB att fördela deras overheadkostnader som de vill, men den ”uppskattade” modellen ger en bas för strategiska beslutsunderlag på produk-tionsenhetsnivå, som svarar på frågor som; var ska man lokalisera produktionsenheter för att nå konkurrensfördelar.

Le véhicule électrique est une des solutions de transport respectueuses de l’environnement, n’émettant pas de polluant lors de son utilisation. Gruau, constructeur carrossier pour véhicules utilitaires, se lance activement dans le transport écologique sur le segment de l’utilitaire 3,5t. Afin d’accroitre les ventes de véhicules utilitaires électriques, il est nécessaire d’en réduire le coût total de possession (ou TCO (Total Cost of Ownership)). L’objectif de cette thèse est d’étudier et de modéliser le comportement des composants de ce véhicule électrique pour simuler des calculs de TCO. Le composant principal étudié est la batterie, dont la durée de vie limitée conditionne la rentabilité du véhicule. La première partie des travaux fut consacrée à la modélisation du comportement du véhicule en fonction d’une mission client donnée. Une étude des cellules de batterie est réalisée dans le but de construire un modèle multi-physique complet en prenant en considération le vieillissement calendaire et le vieillissement en cyclage. Un modèle énergétique global, comprenant ce modèle batterie, permet de déterminer l’énergie nécessaire pour un parcours donné et de simuler le vieillissement des cellules électrochimiques afin de calculer le TCO. Une seconde partie est orientée vers le calcul du TCO. La mise en oeuvre d’un algorithme d’optimisation avec une méthodologie d’accélération des calculs a permis de réaliser les calculs dans des temps raisonnables (passage de 13h à 15min par itération). Après étude de l’impact du dimensionnement de la batterie sur le TCO, il en ressort que la réduction de la capacité n’entraine pas systématiquement la réduction du TCO. Il existe pour chaque mission un point de TCO optimal (jusqu’à 17% d’éconnomie). Afin d’améliorer le TCO, des stratégies de recharge intelligentes sont élaborées et permettent rentabilité accrue du VUE (jusqu’à 29%). Ce travail a été intégré dans un logiciel d’aide à la décision de la capacité de la batterie suivant les besoins du client, destiné aux forces de ventes commerciales
The electric vehicle is one of the environmentally friendly transport solutions that emit no pollutant during its use. Gruau, manufacturer-converter for light commercial vehicles (LCV), is actively involved in green transport in the 3.5t segment. In order to increase sales of electric LCV, it is necessary to reduce its total cost of ownership (TCO). The objective of this thesis is to study and model the behavior of the components of this electric vehicle in order to simulate TCO. The main component studied is the battery, whose limited lifetime will determine the profitability of the vehicle. The first part of the work was devoted to modeling the behavior of the vehicle according to a given customer mission. The study of battery cells was done with the aim of building a complete multi-physics model taking into account calendar aging and cycling aging. Then, this battery model is integrated in a complete energy model taking into account all the components of the studied vehicle. Then a global model, including this battery model, makes it possible to determine the energy required for a given path and to simulate the aging of the electrochemical cells in order to calculate the TCO. A second part is oriented towards the calculation of the TCO. The implementation of an optimization algorithm, with a methodology of computing acceleration, allowed to achieve the computations in reasonable times (reduction from 13h to 15min by iteration). After studying the impact of battery sizing on the TCO, it appears that the reduction of the battery capacity does not systematically lead to the reduction of the TCO. There is therefore an optimum TCO point for each mission (up to 17% savings). In order to improve the TCO, smart recharging strategies are developed and allow increasing e-LCV profitability (up to 29%). This work is integrated into a decision support software relative to the battery capacity according to customer needs, intended for commercial sales forces

All producing companies strive to deliver high-quality products to meet their customers’ requirements, to a reasonable price. In order for the companies to stay competitive, it is important to have an efficient flow through the production and therefore continually analyze and develop their own production. The master thesis was carried out at Strömsholmen AB (SAB), a company which produces and develops gas springs and hydraulic springs. Their production is made by a machining hall and an assembly hall, with a component inventory in between. SAB has a plan to upgrade their surface treatment process, the current bottleneck in the production. The goal with the thesis is to point out the future bottlenecks and constraints, furthermore, propose improvements for a more efficient flow. To discover the improvements, three research questions were asked. The first question refers to map out the current production and map the production when the surface treatment is upgraded. The second question is about finding the next bottleneck in the production with an increased order stock. The last question refers to the finding of improvements and the effects related to the production performance. In order to fulfill the purpose and answer the research questions, a literature survey was conducted and a collection of empirical data. The literature survey provided a connection to the existing theory and the study. The empirical data consists of quantitative data which illustrates the current production, the collected qualitative data gives a more in-depth knowledge about SAB’s production. The data has been collected through observations, semi-structed interviews and documentation. The analyze was built upon the five-why method, to find the root causes in the production. The empirical data established that SAB has a complex material flow through the production and a big assortment of components. Beyond that, the surface treatment process was verified as the current bottleneck of the production. When the surface treatment was upgraded, seven percent capacity was available until next machine group will reach the capacity cap. In the analyze, the current production and potential improvements were compared with the existing theories. The study pointed out the value creating and waste steps of the production and how to adjust the flow according to the value creating and waste steps. Further on, future bottlenecks were pointed out, the bottlenecks could discourage the potential to increase the order stock. Two distinguished results could be established from the analysis. First of all, it would be suitable to implement flow shop for A product’s (stands for 70% of the revenue) components that have the same material flow and go through the same machine groups. This would reduce the production throughput time and enable lower stock levels and thereby decrease the inventory carrying cost. The second result is considering how to eliminate the future bottlenecks in the production, this can be done with either sub-contractors or balance the workload. Consequently, this will enable an 20% increased order stock from the production. In addition to these two major improvements, several other improvements were found during the study which will affect SAB’s potential to gain more profit. The improvements include investigate the quality of their data, start performing forecast and review the number of products and components.

This study considers bicriteria approaches to the minimum cost network flow problem and a rescheduling problem where those approaches find their applications. For the bicriteria integer minimum cost network flow problem, we generate all efficient solutions in two phases. The first phase generates the extreme supported efficient points that are the extreme points of the objective space of the continuous bicriteria network flow problem. In the second phase, we generate the nonextreme supported and unsupported efficient points by Integer Programming Based approaches. Our rescheduling problem considers parallel unrelated machine environments. The criteria are the total flow time as an efficiency measure and the total reassignment cost as a stability measure. We show that the problems that address linear functions of the two criteria can be represented by bicriteria network flow models. To generate all efficient solutions, we use a Classical Approach that is based on the optimal solutions of the singly constrained network flow problem and provide a Branch and Bound approach that starts with extreme supported efficient set and uses powerful bounds. To find an optimal solution to any nonlinear function of the two criteria, we provide a Branch and Bound approach and an Integer Programming Based approach that eliminates some portions of the efficient set that cannot provide improved solutions. We contribute both to the network flow and scheduling literature by proposing algorithms to the bicriteria network flow models and applying them to a rescheduling problem that is bicriteria in nature. The results of our extensive computations with up to 100 jobs and 12 machines have revealed that, the Branch and Bound algorithm finds the efficient set in less computational effort compared to the classical approach. In minimizing a nonlinear function of the two criteria both IP Based approach and Branch and Bound algorithm perform quite satisfactory.

Title: A case study for LORAMAX on supply chain strategy & production efficiency.  Limitations: Due to the sensitive nature of the information in this thesis, a non-disclosure agreement was signed, and some data cannot be disclosed.  Background: LORAMAX, the case company for this thesis produces differentiated products on the basis of quality. They are faced with the challenge of making a product that they recently launched, HERO, more competitive in the market. Even though they have chosen a differentiated strategy, the company understands that cost reduction could as well provide them a competitive advantage and is therefore crucial to the survival of the new product.  Research questions:                How can the production cost and lead time be reduced for HERO? How would the choice to either buy pre-assembled modules or manufacture them in-house influence the profit margin of HERO? Purpose: The purpose of this thesis is to use relevant theories and practical tools in order to help the company identify potential opportunities and areas where to reduce assembly costs and lead-times.  Method: The empirical data used to draw conclusions was collected through a mixed research method (both qualitative and quantitative) carried out on site at LORAMAX with the help of the purchasing and production manager, through interviews, questionnaires and observations. This thesis is written from a positivistic perspective with a deductive approach.  Conclusions: Value Stream Mapping (VSM) and Total Cost of Ownership (TCO) are effective tools for cost and lead time reduction and can be used to support a make-or-buy decision. In this thesis, we arrive at the conclusion that LORAMAX will improve its profit margins on HERO if it buys already assembled modules.

The purpose of this study is to identify main factors when cost estimate is being exceeded in the construction industry both nationally and globally. If the cost estimation is exceeded, it may result in losses for the company, which can be severe and cause extensive damage. Therefore, a study is necessary to see if it is possible to perform a more detailed cost calculation.Cost overruns occur in both bigger and smaller projects. Factors causing cost overruns do not always have to be of the same category. Identifying negative factors as a guideline is troublesome due to the fact that one project outcome might not necessarily be other projects result.In collaboration with Småa AB and our starting point in “The white city”, an examination was performed to identify the factors leading to the costs being exceeded. Study consisting of literature and interviews with the production manager for the White City. At the end of the study the purpose and questions will be answered. Suggestions and solutions will be provided.The work was ongoing during a prevailing pandemic, that has affected the entire world, Covid-19. The pandemic has limited our site visits and interviews. Most of the work has been done digitally.

In the present electrical market there is an increasing penetration of intermittent energy sources. Several studies have examined its effect on the planning of hydropower operation and the conclusion is that an increasing intermittent production is likely to result in a more variable hydropower operation, utilising a wider span of operational set points. The wear of a hydropower unit is generally at a minimum when operated close to best efficiency and increases when operating at higher or lower set points. This study introduces a method to calculate an operation dependent cost (ODC) function for an arbitrary hydropower unit or unit combination based on vibration measurements and operational data. The method is tested in a case study where an ODC is implemented in Akkats, located in the Small Lule River in order to evaluate its effect on operational pattern, profitability and balancing contribution. The results show that the implemented ODC mainly affects Akkats. For an increasing ODC, Akkats is operated closer to the best point of efficiency and the operational pattern gets less variable and the effect gets more apparent the lower the spot price. Akkats ability to follow the spot price is reduced, decreasing the earning per produced energy with a few percent­ages. Akkats balancing contribution decreases significantly more, due to a less variable operational pattern. The study compares the reduced ODC to the reduced spot income and concludes that the wear cost in Akkats has to be above 1,21 €/MWh in order to be economically feasible to include in the planning. The operational pattern for the simulated river is close to unchanged at highest price hours but during lower price hours an increasing ODC results in an increased production, due to an increasing mean flow and changed operational pattern in Akkats. More production during low prices hours results in a decreasing profitability for all plants along the river. The balancing contribution is close to unchanged in all plants except Akkats, since the production still follows the same pattern.

The plastics industry is one of the fastest growing major industries in the world. There is an increase in the amount of plastic used for all types of products due to its light weight and ability to reprocess. For this reason, the reprocessing of thermoplastics and the usability of reprocessed materials are gaining significance, and it is important to produce and consume plastic materials in an environmentally friendly way. In addition, rising raw material cost linked to the increased oil prices encouraged for reusing of the plastic materials. The aim of this research was to study and optimize the injection moulding process parameters to achieve a trade-off between the product cost and product quality, measured through mechanical properties and geometry, based on using regrind ratios. The work was underpinned by a comprehensive study of multiple reprocessing effects in order to evaluate the effect of process parameters, material behaviour, reprocessing effects and possible links between the processing parameters and key properties. Experimental investigations were carried out, in particular, focused on the melt preparation phase to identify key process parameters and settings. Multiple reprocessing stages were carried out; using two types of PP material: unfilled and short glass filled. A series of tests were used to examine product quality (mass, colour and shrinkage) and physical properties (density, crystallinity, thermal stability, fibre length, molecular weight, in-line and off-line viscosity, tensile strength, modulus of elasticity, elongation (%) and flexural strength). This investigation showed that the mouldability of the filled and unfilled PP materials, through the successive reprocessing stages (using 100 % regrind), was observed to be relatively consistent. Given the link between the processing parameters and key product and material properties, it is possible to manufacture products with minimal loss to part quality and mechanical properties. The final phase of the work focused on process optimisation study for short glass fibre filled PP material and the identified key process parameters (melt temperature, screw rotational speed, holding pressure, holding time and injection rate). A response surface experiment was planned and carried out for three reprocessing stages (0 %, 25 % and 50 % regrind). The fitted response surface models were utilised to carry out the trade-off analysis between the operating cost (material cost, energy cost and labour cost) and product quality (dimensions and tensile strength) Based on the optimal moulding conditions, the operating cost was reduced (from stage I as a reference), by 24% and 30 % for stage II and stage III respectively. A small, perhaps undetectable, change in product dimensions was noted. In addition, a small reduction in tensile strength was noted (from stage I as a reference), by 0.4% and 0.1 % for stage II and stage III respectively. The same data was applied in other countries (Australia, USA, Brazil, Libya and China) to manufacture the same product; and it was observed that the cost was reduced with increasing of regrind ratio. But the significant reduction of the cost, essentially, depended on those countries which have low wage rates (e.g. Brazil, Libya and China). For example, the cost of moulded product manufactured in China is £ 0.025 (using 50% of regrind), while the cost of the same product produced in Australia is £ 0.12, hence giving a total saving of 79 % and making it a valuable issue to be considered in industry.

The interruption cost for one hour of a petrochemical plant is 33 times higher than that of the average interruption cost for industrial plants across all industries. In addition to the high cost of loss of production, interruptions to the operations of petrochemical and gas-toliquid plants pose safety and environmental hazards. Thus it is necessary to better understand the reliability requirements of petrochemical and gas-to-liquid plants. This study investigated the reliability of electrical distribution networks used in petrochemical and gas-to-liquid plants compared to those used in other industrial plants. A model was developed that can be used to establish the adequacy of the reliability of a distribution network in terms of the components and network topologies used. This model was validated against data that had been collected by the IEEE and applied to an actual petrochemical plant. Over 19 years’ worth of data regarding the trips that have occurred on the distribution network of an existing petrochemical plant was collected and manipulated in order to calculate the reliability indices associated with the equipment used to make up thisRecommended Practice for the Design of Reliable Industrial and Commercial Power Systems. The cost of loss of production and the capital costs associated with increased reliability were calculated for a section of the existing petrochemical plant. The reliability associated with different network topologies that could possibly be used to supply power to this section of the plant were modelled using an appropriate software package. The resulting total cost of ownership over the life of the plant associated with each topology was then calculated in order to establish which network topology is the most appropriate for petrochemical and gas-to-liquid plants. It was concluded the components that affect the reliability of an industrial distribution network are different to those that affect a utility distribution network. These components were listed and compared. It was found that the reliability indices that were calculated for the components that affect the reliability of a petrochemical plant were similar to those provided by the IEEE. 17 out of 20 of the indices that were calculated were within the required factor of deviation. Generally the failure rates of components used in petrochemical plants were very similar to those given in the IEEE Gold Book, while the MTTR’s for the components used in petrochemical plants were found to be slightly better than those given in the IEEE Gold Book. The effect of network topology was found to be significant, with small changes in the topology of a network resulting in large variations in the reliability of the network. It was also found that the most appropriate type of network topology to use in the design of the electrical distribution network of a petrochemical plant is the dual radial network. This is the most conservative of the commonly used network topologies and is the one that is currently used in the existing plant that was studied. Due to the high cost of loss of production in petrochemical plants it was established that any incremental improvement in the reliability of the dual radial network would be beneficial to the total cost of ownership of such a plant. Such incremental improvement of the reliability of the distribution network could be cost effectively achieved by adopting a conservative maintenance strategy and the establishment of a conservative spares inventory. Before this study was undertaken, there was no literature around the reliability of electrical distribution networks that focused specifically on petrochemical and gas-to-liquid plants. This study produced a set of reliability indices and a model that electrical engineers can use in the reliability analysis of petrochemical and gas-to-liquid plants. Furthermore it shows that, because the cost of loss of production in petrochemical plants is so high, the most conservative distribution network design and maintenance philosophies should always be used. distribution network. These reliability indices were compared to those given by the IEEE
Dissertation (MEng)--University of Pretoria, 2013.
gm2014
Electrical, Electronic and Computer Engineering
unrestricted

Diante de um crescimento econômico, as empresas de maneira geral e, em particular, a indústria de manufatura, acabam procurando um meio de eliminar perdas que estão em evidência e outras que não estão tão expostas, para assim maximizar seus lucros. Este trabalho mostra uma programação de produção otimizada, de modo a aumentar a disponibilidade de um equipamento responsável em manufaturar mais de um modelo de produto. Com exigências cada vez maiores, os consumidores obrigam a indústria a variar seu mix de produção de modo a não poder mais possuir equipamentos dedicados para cada tipo de modelo produzido. Com isso, exige-se cada vez mais o uso de abordagens de pesquisa operacional para poder montar um cronograma de produção de forma mais rápida e assertiva. Não se pode deixar de considerar a influência da disponibilidade do equipamento para o bom andamento da programação da produção. Alinhado a isto ao avaliar as maiores perdas de um equipamento, verifica-se a necessidade de se reduzir seu tempo de set-up. Para que isto seja possível, é sugerida a aplicação da metodologia SMED, a qual foi criada dentro do sistema Lean Manufacturing, mais especificamente do sistema TPM. Do ponto de vista da otimização, o problema proposto é desafiador, já que há múltiplos processadores idênticos, em paralelo e o set-up entre os produtos é dependente da sequência de produção. Assim, cabe ao sistema proposto definir quanto da demanda total de cada produto será produzida em cada um dos processadores, visando a minimização do tempo total de set-up. Ou seja, os lotes de produção não têm tamanho fixo. Foi proposta uma abordagem híbrida usando regras de despacho (heurísticas) para a solução do problema proposto, com resultados satisfatórios.
Due to economic growth, companies in general – but particularly manufacturing industries - end up looking for a way to eliminate losses that are evident and others that are not so easy to identify so as to maximize profits. This project seeks for an optimal production schedule to increase the availability of a device responsible for manufacturing more than one product. With increased demands from customers, industry is compelled to vary its production mix so that it can not have equipment dedicated to each produced model type. Thus, the use of operational research approaches is more and more required to be able to set up a production schedule in a faster and assertive way. One can not stop considering the influence of equipment availability for a smoother production scheduling. Aligned with this, when evaluating the major losses at the equipment, there is a need to reduce the set-up time. To make this possible, it is suggested the implementation of the SMED methodology, which was created within Lean Manufacturing - more specifically, by TPM system. From the perspective of optimization, the proposed problem is challenging since there are multiple identical parallel processors with sequence dependent set-ups. Thus, it is up to the proposed system to define how much of the total demand for each product will be produced in each of the processors in order to minimize the total set-up time. In other words, production lots have no fixed size. It was proposed a hybrid approach using dispatch rules (heuristics) for the solution of the proposed problem that have presented satisfactory results.

L’objectif de ces travaux est de développer une méthode d’aide à la conception des réseaux de chaleur urbains (RCU). Cette méthode utilise un modèle de type MINLP (Mixed Integer Non Linear Programming) pour l’optimisation simultanée de la configuration et du dimensionnement d’un RCU. Aux variables continues pour l’aide au dimensionnement (température, vitesse, diamètre, aire des échangeurs), s’ajoutent des variables binaires aidant à définir la configuration du réseau (maillage et choix des technologies). La fonction objectif à minimiser est le coût total (capex et opex), qui est soumise à un ensemble de contraintes non linéaires (p. ex. pertes thermiques et de charge, bilans). La méthode développée dans ce manuscrit offre la possibilité de connecter en cascade des consommateurs n’ayant pas les mêmes besoins en température, et de réaliser des réseaux bouclés (une canalisation par tranchée). Elle permet aussi de choisir : les consommateurs à connecter au RCU, le ou les sites de production ainsi que le type de technologie utilisée. Enfin la bonne prise en compte de la physique permet de choisir le meilleur compromis entre pertes thermiques et pertes de charge, sur une large gamme de température. Cette formulation permet donc d’optimiser des réseaux de 4éme génération et de démontrer la rentabilité de l’intégration d’EnR&R sur le long terme (30 ans). Un premier travail est réalisé afin de proposer une méthodologie de résolution en plusieurs étapes permettant l’obtention de l’optimum global. Différents cas d’études académiques sont utilisés pour présenter les intérêts multiples de cette formulation. Enfin la comparaison avec un réseau existant a permis de démontrer la cohérence des résultats du modèle et a servi de base pour l’optimisation d’un cas d’étude de grande dimension. Plusieurs études de sensibilité post-optimale sont réalisées afin de démontrer l’intérêt de cet outil pour l’aide à la conception initiale ou l’extension de RCU existants
The aim of this thesis is to develop a method that provides design assistance for District Heating Network (DHN). This tool allows simultaneously the optimization of the configuration and its sizing, thanks to an MINLP formulation (Mixed Integer Non-Linear Programming). Binary variables help to choose the optimal configuration (network layout and technologies of production), whereas continuous variables help DHN sizing (temperature, diameter, velocity, heat exchanger area, thermal generating capacity …). The objective function to minimize is the total cost (capex and opex), subjected to numerous nonlinear constraints (e.g. thermal losses, pressure drop, energy balance).This method enables to design temperature cascade between consumers, when consumer temperature requirements are different, and also looped network (only one pipe in one trench). It helps also the decision to connect (or not) consumers to the main network and also the location(s) and type(s) of the heating plant. Moreover, the arbitrage between heat losses and pressure drops is taken into account thanks to physical considerations (non-linear equations). Eventually, it is possible to design 4th generation DHN and prove their financial profitability over the long terms (30 years). First a multi-step resolution strategy is proposed to ensure finding global optimum of the complex MINLP problem. Then academic study cases are analyzed to underline the numerous assets of the formulation. Finally, the optimal design compared to an existing DHN ensures the consistency of the method and allows to build a study case at a wider scale, which can be solved thanks to the comprehensive strategy developed. The design assistance method is available for initial design as well as for extension of existing DHN

La contribution des sources d'énergie renouvelables dans le mix de la production d'électricité augmente largement. De ce fait, l'intégration des technologies de stockage d'énergie dans le réseau électrique devient inévitable afin de remédier aux inconvénients des sources renouvelables. Ainsi, l'objectif de cette thèse est d'évaluer la rentabilité, d'optimiser et d'étudier le comportement dynamique d'un cycle adiabatique de stockage d'énergie par air comprimé fonctionnant à pression fixe (IA-CAES). Ce système est caractérisé d'une part par la récupération de la chaleur de compression et d'autre part par le stockage d'air comprimé sous pression fixe dans des réservoirs hydropneumatiques. Ceux-ci permettent d'améliorer l'efficacité et la densité énergétiques du système de stockage et d'éviter l'utilisation de sources d'énergie fossiles.Tout d'abord, un modèle statique est développé pour achever des analyses énergétiques et exergétique du système IA-CAES. Un modèle exergoéconomique est également réalisé dans le but d'optimiser la rentabilité du système de stockage en utilisant un algorithme génétique. Ainsi, une fonction objective, qui prend en compte le coût d'investissement et le coût d'exploitation, est définie pour être minimisée. L'efficacité du système est de 55,1% dans le cas de base, elle est améliorée à 56,6% après optimisation avec une diminution du capital investi de 5,6%.D'autre part, un modèle dynamique est développé pour étudier la flexibilité du système de stockage et sa capacité à répondre aux besoins du réseau électrique (réserves primaires et secondaires) en évaluant la durée des phases transitoires. Les résultats montrent que le système de stockage a besoin d’un temps supérieur à 2 min avant de pouvoir consommer tout l'excès d'énergie disponible sur le réseau électrique et supérieur à 5 min avant d'être capable de produire toute l'énergie requise par le réseau électrique. Des suggestions sont analysées dans l'objectif d'améliorer la flexibilité du système de stockage tel que le fonctionnement du système en mode de veille avec des vitesses réduites. Il permet de réduire les pertes d'énergie de 68% en mode de stockage et de 27% en mode de production par rapport au mode de veille en vitesses nominales
The contribution of the renewable energy sources in the electricity generation mix is greatly increasing. Thereby, the integration of the energy storage technologies into the electrical grid is becoming crucial to reduce the drawbacks of the renewable energy sources. Then, the objective of this thesis is to evaluate the cost-effectiveness, to optimize and to study the transient behavior of a novel isobaric adiabatic compressed air energy storage (IA-CAES) system. This plant is characterized by the recovery of the compression heat and the storage of the compressed air under fixed pressure in hydro-pneumatic tanks. These allow improving the efficiency and the energy density of the storage system and avoiding the use of fossil fuel sources.Firstly, a steady state model is developed to perform energy and exergy analyses of the IA-CAES system. An exergoeconomic model is also carried out in order to optimize the cost-effectiveness of the storage system by using a genetic algorithm. So, an objective function, which includes the investment cost and the operating cost, is defined to be minimized. The system efficiency is 55.1% in the base case, it is improved to 56.6% after optimization with a decrease in the capital investment by 5.6%.Secondly, a dynamic model is developed to study the flexibility of the storage system and its ability to meet the electrical grid requirements (primary and secondary reserves) by evaluating the duration of the transient states. The results show that the storage system needs more than 2 min before being able to consume all the excess energy available on the electrical grid and more than 5 min before being able to produce all the energy required by the electrical grid. Suggestions are analyzed to improve the flexibility of the storage system such as the operation of the storage system in standby mode with low speeds. It allows reducing the energy losses by 68% during the storage mode and by 27% during the production mode compared to the standby mode in nominal speeds

Syfte – Studiens syfte var att utveckla KDI-metoden till att även inkludera egentillverkade artiklar. För att kunna uppfylla syftet har det brutits ned i tre frågeställningar: Vilka data och analysverktyg i KDI-metoden berör egentillverkade artiklar? Vilka verktyg bör tillkomma i fas två för att kunna analysera egentillverkade artiklar? Vilken ytterligare data bör tillkomma i fas ett för att kunna inkludera egentillverkade artiklar? Metod – Tillvägagångssättet för studien innefattade en litteraturstudie, en fallstudie samt en analytisk konceptuell ansats. För att besvara den första frågeställningen genomfördes fallstudien innehållande intervjuer, observationer samt dokumentstudier på fallföretaget Kinnarps, Skillingaryd. Insamlad data tolkades och analyserades i förhållande till ett teoretiskt ramverk som genererade ett resultat. För att besvara den andra och tredje frågeställningen genomfördes en analytisk konceptuell ansats utifrån tidigare framtagna teorier som senare sammanställdes i en modell. Resultat – Steg ett till fyra i fas ett samt steg sju och åtta i fas två i KDI-metoden berör egentillverkade artiklar. En modell för inkludering av egentillverkade artiklar skapades där det framgår vilka analysverktyg samt data som bör undersökas. De verktyg som tagits fram baseras på teorier kring bland annat värdeflödeskartläggning, materialhantering och modell för make-or-buy beslut. Utifrån dessa verktyg kunde det tolkas vilka data som bör tillkomma för egentillverkade artiklar. Implikationer – I denna studie framgår det att ingen ny litteratur har upprättats utan kombinationer av redan existerande teorier presenteras. Teorin kring KDI-metoden skulle kunna förändras utifrån det sidoresultat som presenteras i examensarbetets sjunde kapitel. Verksamheter som applicerar KDT-metoden skulle kunna öka kunskapen för KDT och därmed förbättra verksamheten internt. Metoden hjälper även till vid analys för både externa och interna flöden. Begränsningar – KDI-metoden är i nuläget relativt ny och ej testad utanför det kontext som den är utformad för. Detta har resulterat i att författarna ej har kunnat styrka denna litteratur utifrån andra forskare. Fokus har legat på att finna teorier till kunddriven tillverkning kring värdeflödeskartläggning, materialhantering med mera. Önskvärt hade varit att genomföra ytterligare litteraturstudier för att finna lämpliga utvecklingsområden. Nyckelord – KDI-metoden, materialhantering, SWOT-analys, försörjningskedja, värdeflödeskartläggning, produktionslayout.
Purpose – The purpose of the study was to develop the CDP-method to include also manufacturing items. In order to help answering the purpose, three questions have been defined: Which data and analytical tools in the CDP-method affect manufactured items? Which tools should be added in the second phase in order to analyse manufactured items? Which additional data should be included in the first phase in order to include manufactured items? Method – The procedure for the study contain a literature study, case study and an analytical conceptual approach. In order to answer the first question, a case study was performed with interviews, observations and document studies at Kinnarps, Skillingaryd. The received data were interpret and analysed in relation to the theoretical framework that generated a result. In order to answer the second and third question, an analytical conceptual approach were conducted from previous theories that later was compiled in a model. Findings – Step one to four in the first phase and step seven and eight in the second phase of the CDP-method affect manufactured items. A model for included manufactured items has been created where analytical tools and data are presented that should be investigated. The tools that are introduced are based on theories within value stream mapping, material handling and a model for make-or-buy-decision. Based on these tools, it could be interpreted which data that should be created for manufactured items. Implications – It appears in this study that no new literature has been created but combinations of already existed theories are presented. The theory within the CDP- method could be changed from results that were founded when the CDP-method was applied at the case company. This is presented in the bachelor thesis seventh chapter. Companies that apply the CDM-method could increase the knowledge for customer driven manufacturing and improve the company internally. The method also assists when analysing both external and internal flows. Limitations – Today the CDP-method is relative new and not applied outside the context that it is designed for. One result of this is that the authors have not confirmed these literatures by other researcher. The focus has been to find theories to customer driven manufacturing within value stream mapping material handling and so on. It would have been desirable if additional literature studies could be performed in order to find appropriate development areas. Keywords – CDP-method, material handling, SWOT-analysis, supply chain, make- or-buy analysis, value stream mapping, production layout, total cost of ownership.

L'hydrogène est l'un des vecteurs énergétiques les plus prometteurs dans la recherche d'un mix énergétique plus durable. Plusieurs études et feuilles de route ont été réalisées sur le potentiel d'une économie « hydrogène » et ont identifié que même si de nombreuses technologies requisessont déjà disponibles aujourd'hui, le déploiement d'infrastructures hydrogène constitue la tâche la plus difficile de son développement, dont la mesure où on doit atteindre des coûts compétitifs et avoir l'acceptation du marché. La conception de la chaîne logistique de l’hydrogène (HSC), enparticulier à des fins de mobilité, implique une série de décisions importantes à différents niveaux (sources d'énergie, production, transport et stockage) et peut être considérée comme un problème multi-échelle et multi-période avec plusieurs parties prenantes. L'objectif de ce travail est de proposer un cadre méthodologique pour aborder le problème de conception de la HSC de manière complémentaire au travail proposé dans le travail de doctorat de (Sofia de Leon Almaraz, 2014) dans lequel une formulation multi-objectif a été mise en œuvre via la méthodologie - contrainte pour obtenir le front de Pareto, en optimisant trois objectifs en même temps : le coût journalier total, le potentiel de réchauffement global et un indice de risque de sécurité. Une analyse de sensibilité basée sur un plan d'expérience en utilisant les méthodes de plan factoriel et surface de réponse a été réalisée pour identifier les principaux paramètres (facteurs) et leur interaction affectant le critère économique, soit le coût journalier total (TDC) (réponse), englobant les coûts capitaux et opérationnels. Cette analyse de sensibilité souligne que la demande est de loin le paramètre le plus important qui conditionne fortement le critère TDC, de sorte que davantage d'efforts sont nécessaires pour modéliser l'incertitude de la demande de façon homogène. Dans la formulation initiale de la conception de la HSC, la taille du problème liée au nombre de variables binaires conduit souvent à des difficultés pour résoudre le problème. Dans ce travail, le potentiel des algorithmes génétiques (GA) via une variante de NSGA-II est exploré pour faire face à la formulation multi-objectif, afin de produire automatiquement le front de Pareto. La formulation du modèle a ensuite été étendue pour tenir compte de l'incertitude de la demande, ce qui donne plus de robustesse à l'approche proposée. Deux études de cas soutiennent cette analyse : d'abord au niveau régional, les résultats de la conception de la HSC pour l'ancienne région Midi-Pyrénées obtenus avec les deux modèles sont comparés. Les solutions obtenues par GA présentent le même ordre de grandeur que celles obtenues avec MILP (Programmation Linéaire en Nombres Entiers) dans le problème mono-critère, mais de meilleures solutions de compromis sont produites dans la formulation multi-objectif et des résultats plus flexibles sont obtenues avec la modélisation de l’incertitude de demande. Puis l’écosystème aéroportuaire, Tarbes-Lourdes, a été étudié : l'infrastructure aéroportuaire est une étude de cas intéressante, car un aéroport est une source d'émissions qui affectent le climat à cause des émissions générées par les activités faites à l'intérieur et à l'extérieur du périmètre de l'aéroport, liées à l’opération et utilisation de l’aéroport. Enfin, une analyse post-optimale sur une solution de compromis de la HSC est réalisée sur la base d'une évaluation sociale, via deux analyses coûts-bénéfices (CBA) d'un point de vue social (SCBA) et gouvernemental (subventions et taxes), montrant que l'incorporation d'externalités aide à financer une proportion importante des coûts. L'approche SCBA pour le déploiement de l'hydrogène intègre les avantages sociétaux induits à travers la réduction des émissions de gaz à effet de serre, la réduction de la pollution atmosphérique mais aussi les coûts sociaux par l'augmentation de la consommation de platine
Hydrogen is one of the most promising energy carriers in the quest for a more sustainable energy mix. Several studies and roadmaps have been carried out about the potential of a « hydrogen » economy and have identified that even if many of the required technologies are already available today, the deployment of hydrogen infrastructures constitutes the most challenging task for its development, so as to achieve competitive costs and mass market acceptance. The design of a hydrogen supply chain (HSC), in particular for mobility purpose, involves a series of important decisions at different levels, i.e. energy sources, production, transportation and storage and can be viewed as a multi-echelon, multi-objective and multi-period problem with multiple stakeholders. The objective of this work is to propose a methodological framework to tackle the HSC design problem in a complementary manner to the work proposed in the PhD work of (Sofia de Leon Almaraz, 2014) in which a multi-objective formulation was implemented via the -constraint method to generate the Pareto front, optimising three objectives at the same time, total daily cost, global warming potential and a safety risk index. A sensitivity analysis based on a design of experiments through the Factorial Design and Response Surface methods was carried to identify the major parameters (factors) and their interaction affecting the economic criterion, i.e., the total daily cost (TDC) (response), encompassing capital and operational expenditures. This sensitivity analysis highlights that the demand is by far the most significant parameter that strongly conditions the TDC criterion so that more effort is needed to model demand uncertainty consistently in HSC design, especially since a long horizon time is considered for hydrogen deployment. Besides, in the initial formulation of HSC design, the size of the problem related to the number of binary variables often leads to difficulties for problem solution. In this work, the potential of genetic algorithms (GA) via a variant of NSGA-II is explored to cope with the multi-objective formulation, in order to automatically produce the Pareto front. The model formulation has then been extended to take into account demand uncertainty, giving more robustness to the proposed approach. Two case studies support the analysis: first at regional level, the results of a HSC design for the former Midi-Pyrénées region obtained with both models are compared. The solutions obtained by GA exhibit the same order of magnitude as those obtained with MILP (Mixed Integer Linear Programming) in the mono-criterion problem, but better compromise solutions are produced in the multi-objective formulation and more flexible ones are obtained with demand uncertainty modelling. Then an airport ecosystem, i.e. Tarbes-Lourdes has been studied: the airport infrastructure is an interesting case study, since an airport is a source of emissions that affect climate, including the emissions generated from activities occurring inside and outside the airport perimeter fence associated with the operation and use of an airport. Finally, a post-optimal analysis on a compromise solution of HSC configuration is carried out based via two cost-benefit analyses (CBA) from a social (SCBA) and governmental perspective (subsidies and taxes). The SCBA approach for hydrogen deployment integrates societal benefits for the reduction of greenhouse gas emissions, noise air pollution abatement and social costs for the increase in platinum consumption in the manufacture of fuel cells. By including external costs, economic benefits of the replacement of ICEV (internal combustion engine) by FCV (Fuel Cell Vehicles) were highlighted as well as the generation of positive social net present values

Les bus électriques à batterie (BEB) représentent une solution prometteuse pour remplacer les flottes de bus diesel actuelles consommant des énergies fossiles grâce à leur efficacité énergétique élevée et à leur potentiel de réduction des émissions de gaz à effet de serre et à l’absence d’émissions de polluants atmosphériques locaux. Cependant, cette technologie doit faire face à plusieurs défis, en particulier le coût total de possession (TCO) élevé et des contraintes opérationnelles comme l’autonomie des bus, le temps et le lieu de recharge. Cette thèse présente une méthodologie systématique qui vise à développer des solutions pour surmonter ces défis en fournissant un dimensionnement des batteries et une stratégie de recharge optimales pour les BEB. D'abord, un modèle énergétique multi-physique de bus est développé pour évaluer ses besoins énergétiques en prenant en considération ses différents systèmes énergétiques. Ensuite, la consommation d'énergie du bus est évaluée dans plusieurs conditions de fonctionnement afin de quantifier sa consommation d'énergie réelle. Un modèle techno-économique d'une ligne de bus est développé afin d'évaluer l'impact des différentes stratégies de dimensionnement et de recharge des batteries sur les coûts et le fonctionnement du BEB. Ensuite, un modèle TCO est introduit en tenant compte les coûts unitaires BEB, les coûts d'achat et de remplacement des batteries, les coûts d'électricité, les coûts d'infrastructure et de maintenance. L'analyse des résultats d’un cas d’étude à Paris souligne les compromis entre le TCO et les perturbations et les retards des horaires du BEB en fonction des différentes tailles de batterie et stratégies de recharge. Enfin, une méthodologie minimisant le TCO est proposée en déterminant un dimensionnement des batteries et une stratégie de recharge optimales pour la flotte de BEB tout en garantissant l'absence de perturbation des horaires ou des interruptions du service. Elle repose sur une optimisation en deux étapes qui utilise à la fois la programmation dynamique et un algorithme génétique. Les résultats montrent que la méthodologie proposée pourrait réduire le TCO du BEB entre 15-25% par rapport aux approches actuellement adoptées
Initiatives to decrease emissions from the transport sector are increasing worldwide by seeking alternative technologies to replace oil-based mobility. Battery Electric Buses (BEB) present a promising solution thanks to their high energy efficiency, low greenhouse gas emissions and the absence of local pollutant emissions. However, this technology still faces many challenges, especially its high total cost of ownership (TCO) and other operational factors such as the limited bus driving range, the high energy refueling time, and the required charging technologies and strategies. In this context, this thesis presents a systematic methodology that aims at developing solutions to help overcoming these challenges by providing optimal battery sizing and charging strategy for BEB. First, a comprehensive multi-physical bus energy model is developed to evaluate its energy needs considering all the energy systems encountered within. The energy consumption of the bus is then evaluated at a variety of operating conditions. Then, a techno-economic model of an entire bus line is developed in order to assess the impact of different battery sizing and charging strategies on the costs and operation of BEB. A TCO model is introduced considering the BEB unit costs, battery purchase and replacement costs, energy and power costs, infrastructure, and maintenance costs. A case study in Paris city is presented and the analysis reveals the resulting tradeoff between the TCO and BEB schedule disruptions and delays as function of different battery sizes and charging strategies. A methodology to minimize the TCO of BEB deployment is presented providing the optimal battery sizing and charging strategy for BEB, while respecting the BEB operation constraints. The methodology is a 2-step optimization algorithm that utilizes both Dynamic programming and Genetic Algorithm optimization routines. The results show that the proposed methodology could reduce the BEB TCO between 15-25% compared to the currently adopted approaches to deploy BEB

This diploma thesis mainly deals with valuation of steel structures from the perspective of an investor. Today there are several types of steel constructions, which assemble is partly done in workshop, so called “bridge-workshop”, and the rest of the assembling is done directly at the building site. That is the main difference from the construction industry. This fact makes financial valuation of whole thesis very difficult, because construction companies often do not state detailed breakdown of their activities. The main goal of this thesis is to suggest procedure how to value steel constructions in a phase of documentation processing, workshop production, transportation and technological equipment construction at the site.

碩士
國立雲林科技大學
工業工程與管理研究所碩士班
101
In the current the supply chain has many kinds of distribution center, and try their best to cost down; however they have many different kinds and also have different fitness strategies, not push-based Supply chain, but pull-based supply chain, and in the pull-based supply chain, how to respond they require is the most important point, and production scheduling and vehicle routing problem are concentrated by the research of the past, but most of them are considered separately; and there is some literature to integrate the production scheduling and vehicle routing problem, but all of the above are focus on how to combine the require and reduce the total deliver times, and the condition appears to the global supply chain or between locations; this research and the literature are different, and it’s appearing at the upward integration distribution center, and focus on how to reduce the vehicle operating cost, routing cost, and earliness, lateness cost. The research mainly discusses distribute in location, and integration production scheduling and vehicle routing problem; the environment considers a pull-based distribution, that is distribution center have multiple customers and requires are known, and objection is how to make the total cost to minimize.

碩士
國立雲林科技大學
工業工程與管理系
104
In 21st century, the industry is confronted with a huge demand of the consumers. In the fierce competition environment, the supplier must careful considering, how to fast respond customers require. The study presents the minimized total cost of the integrating multi-periodic production and multi-periodic distribution. There is some literature to integrate the production scheduling and vehicle routing problem, but some of the study either consider the single period distribution and complex production, or the multi-periodic production and single production. In order to have a more comprehensive discussion, the study consider the above two points, unrelated parallel machine in the production environment, the multi- periodic in the distribution. The study uses a local search approach, with Particle Swarm Optimization (PSO) algorithm to solve the problem. Through experimental design to compare with differences of the tradition particle swarm optimization and the proposed heuristic particle swarm optimization, confirmed on solving this problem. And the proposed method can indeed give consideration to the quality.

碩士
國立雲林科技大學
工業工程與管理系
102
The supply chain is an important part when distributing products to customers. The supply chain includes production scheduling and vehicle route planning two parts. The traditional method of production scheduling usually made by production factory to ensure the scheduling could satisfy the demand order, and vehicle route planning usually made by distribution center to ensure the demand order could send in time. The goal of the two planning is different, one is production orientation, and the other is customer orientation. However, many scholars presented that the problem could be integrated together these years. We can considered the products features in the problem to minimize the total cost or maximize the total profit. The research considered the production scheduling, vehicle route planning, and product due day penalty in a problem. The demand information is known to make the production and distribution decision to minimize the total cost.

Population escalation in the developing world has been associated with increased poverty, food insecurity and environmental degradation. The situation in Rwanda, with 2.82% annual population increase is no exception. The objective of the present study was to investigate an innovative integrated system of sustainable production suitable for resource-poor rural farmers, the Integrated Rabbit–Fish–Rice (IRFR) system. The study was targeted towards contributing to Rwanda government’s goals of eradicating extreme poverty and hunger, enhancing food security as well as abating environmental degradation. Three experiments, were carried out between 2008 and 2010, and designed to fertilise pond water with rabbit droppings and boost phytoplankton production. We also used results from our previous study, conducted in 2005 in the same ponds and under similar experimental conditions, especially rabbit and fish species and age, fishpond dimensions, as well as the fertilisation mode. The fishpond effluent was re-used to irrigate rice fields rather than being discharged into the environment. This study advocated the potential adaptation of rabbits to wetland conditions and the role of rabbit droppings as organic fertilisers in providing a better environment for fish production. On-farm resources, including rabbit droppings, were the main source of nutrients in the system. The analysis of nutrient flow revealed that 27% N and 79% P of the total nitrogen and phosphorus in fertilizing input in fishponds were supplied by rabbit droppings only. Nile tilapia Oreochromis niloticus were able to recover 18.5–37.6% N and 16.9–34.3% P of the total nitrogen and phosphorus inputs, the rest being accumulated in the pond water and the sediment, making them useful for soil fertilisation. The re-use of nutrient-rich effluent in rice irrigation increased rice production, allowing a successful complete substitution of inorganic fertilisers. The irrigation also reduced environmental pollution as the water seeping through rice field was 31.8 and 83.3% less concentrated in total phosphorus and nitrite pollutants, respectively, than was the pond water. Economically, the IRFR generated up to 597% net return over that of the rice inorganically fertilised, thereby substantiating the sustainability of the system. Overall, it is concluded that the IRFR system works well, is readily applicable, and capable of high, diversified, and sustainable production on limited land. As such, the study demonstrates the potentialities of the IRFR system to contribute successfully to poverty reduction, and the enhancement of food security in rural areas. The system promises economic returns and is environmental friendly. The research recommends the optimal range of rabbit density, that is, 800–1200 rabbits per hectare of pond, and the best fish stocking density, that is, 3 fish.mˉ², for a sustainable IRFR culture system.
Thesis (Ph.D.)-University of KwaZulu-Natal, Pietermaritzburg, 2011.

yes
This work describes how the design and operation parameters of the Multi-Stage Flash (MSF) desalination process are optimised when the process is subject to variation in seawater temperature, fouling and freshwater demand throughout the day. A simple polynomial based dynamic seawater temperature and variable freshwater demand correlations are developed based on actual data which are incorporated in the MSF mathematical model using gPROMS models builder 3.0.3. In addition, a fouling model based on stage temperature is considered. The fouling and the effect of noncondensable gases are incorporated into the calculation of overall heat transfer co-efficient for condensers. Finally, an optimisation problem is developed where the total daily operating cost of the MSF process is minimised by optimising the design (no of stages) and the operating (seawater rejected flowrate and brine recycle flowrate) parameters.

The traditional quality culture in the pharmaceutical industry is driven by the regulatory process of marketing authorisation and manufacturing authorisation. These components of the South African regulatory control system are exclusively technically-orientated, with no managerial focus. This study identifies several quality management principles which could find general application in the pharmaceutical industry. The research compares the current regulatory control system with the total quality concept, and highlights the positive contribution which the total quality approach is able to make in terms of its field of reference; the strategic business value of quality; quality policy formulation; the quality organisational structure; enhanced operations management; and management's control over quality costs, in particular
Economic & Management Sciences
M.Com. (Business Economics)

Кваліфікаційна робота магістра складається з трьох розділів. Об’єкт дослідження – ПАТ «ОЗГТВ». У роботі розглядаються теоретичні аспекти oбліку і аудиту витрат у системі управління підприємствами, визначено дискусійні питання обліку операційних витрат в сучасних умовах, запропоновано екoнoмікo - математичне моделювання процесів формування і відображення витрат підприємства визначено недоліки діючої на базовому підприємстві методики обліку та аудиту витрат і запропоновано шляхи їх усунення. Проаналізовано діючу практику обліку і аудиту витрат на об’єкті дослідження, проаналізовано основні фінансово-економічні показники діяльності ПАТ «ОЗГТВ». Запропоновано Шляхи удосконалення методики обліку і аудиту витрат в сучасних умовах, надано перелік основних рекомендацій щодо можливих заходів з оптимізації операційних витрат з метою покращення фінансового стану базового підприємства.
The thesis consists of three chapters. The object of study is Public Joint Stock Company «OZGTV». Thesis deals with theoretical aspects of accounting and auditing of costs in the enterprise management system, discussing issues of accounting of operating expenses in modern conditions, defining economic - mathematical modeling of processes of formation and reflection of costs of the enterprise, deficiencies of the method of accounting and auditing of operating costs at the base enterprise are offered and and suggests the ways of their elimination. Author analysis current practice of book keeping and control of operating expenses at the research object, analyses the main financial and economic indicators of activity of the Public Joint Stock Company «OZGTV» Author Ways to improve the methodology of accounting and audit of costs in modern conditions, a list of basic recommendations on possible measures to optimize operating expenses in order to improve the financial condition of the parent enterprise Author offers ways of improvement of book keeping and operating expenses control of condition and movement system in current conditions and carries out economic-mathematical modelling of stocks purchasing optimization possibilities.