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Academic literature on the topic 'Industrial management Australia Mathematical models'

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Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Industrial management Australia Mathematical models"

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Iwanowicz, Damian. "Assessment of selected methods of estimating the maximum back-of-queue size on a signal-controlled intersection approach." Journal of Civil Engineering and Transport 4, no. 2 (December 31, 2022): 49–63. http://dx.doi.org/10.24136/tren.2022.008.

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The article presents the characteristics and evaluation of the accuracy of estimating the maximum length of the queue of vehicles at signalized intersections by commonly used methods in the world. The analyzes were based on the latest editions of the guidelines in the United States, Canada, Australia, Germany and Poland. In order to carry out accuracy analyzes, traffic tests were carried out at 5 intersection inlets in three different cities in Poland (Bydgoszcz, Torun, Warsaw), covering all phases of vehicle queue formation during individual periods of the signaling cycle (effective red and green signal). In total, the analysis had the results of tests from 81 hours of observation ~23,000 behaviors of vehicle drivers. Based on the analyzes it was found in particular: (1) slight differences in the construction of mathematical models of the considered calculation methods, with the exception of the US HCM model from 2016; (2) small errors in estimating the maximum queue length in unsaturated vehicle flow states (~3-5 vehicles/cycle and ~2-6 vehicles/15 minutes interval); (3) quite large errors in estimating the maximum queue length in saturated and oversaturated vehicle flow states (~11-16 vehicles/cycle and ~15-18 vehicles/15 minutes interval); (4) the main impact on estimation errors in oversaturation traffic states is not taking into account or incorrect determination of the 'so-called' initial queue length of the period preceding the analyzed period.
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Pop, Viorel. "Mathematical Models Issues of Environmental Management." Studia Universitatis „Vasile Goldis” Arad – Economics Series 25, no. 1 (May 1, 2015): 60–73. http://dx.doi.org/10.1515/sues-2015-0005.

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Abstract Today the world is facing, more and more, different sources of pollution, the most affected areas being the proximity of big industrial centers (e.g.: chemistry, mining and metallurgy, machinery building etc.). Baia Mare industrial area is a typical one for such a situation. To maintain a clean and healthy environment in Baia Mare city and in the surrounding areas, important costs are needed. The usefulness of the mathematical models consists in the possibility of mathematical processing of industrial parameters evolutions, with relevant interpretations on various influences and their correction for achieving the set goals (maximizing financial efficiency, environmental protection with the compliance of legal requirements etc.)
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Stroev, S. P. "Mathematical models for insolvency risk management of an industrial enterprise." CONTINUUM. MATHS. INFORMATICS. EDUCATION, no. 2 (2021): 89–98. http://dx.doi.org/10.24888/2500-1957-2021-2-89-98.

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Eggersmann, M., L. von Wedel, and W. Marquardt. "Management and Reuse of Mathematical Models in the Industrial Design Process." Chemical Engineering & Technology 27, no. 1 (January 9, 2004): 13–22. http://dx.doi.org/10.1002/ceat.200406114.

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Aliyeva, Nailya Rauf kyzy. "Economic and Mathematical Modeling of the Innovation Process in the Agro-Industrial Sector." Economic Herald of the Donbas, no. 2 (64) (2021): 118–22. http://dx.doi.org/10.12958/1817-3772-2021-2(64)-118-122.

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Modern scientific research in the agro-industrial sphere is increasingly based on various mathematical calculations. In practice, it is economic and mathematical models that are of particular importance. These methods and approaches have gained particular value and distribution in the production environment, but in modern conditions of production and economic activity, more and more sectoral economic entities are faced with the application of mathematical models in order to improve the efficiency of investment resource management.
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Alieva, N. "Economic and Mathematical Modeling of the Innovation Process in the Agro-Industrial Sector." Economic Herald of the Donbas, no. 4 (66) (2021): 29–32. http://dx.doi.org/10.12958/1817-3772-2021-4(66)-29-32.

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Modern scientific research in the field of agriculture is increasingly based on various mathematical calculations. In practice, it is the economic and mathematical models that are of particular importance. These methods and approaches are particularly valuable and widespread in the production environment, but in the modern conditions of production and economic activity, more and more industrial economic entities are faced with the application of mathematical models in order to improve the efficiency of investment resource management.
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Topolsky, N. G., A. V. Mokshantsev, E. A. Meshalkin, A. I. Ovsyanik, V. V. Simakov, V. V. Kafidov, and Do Hoang Thanh. "Models and algorithms for automated search and rescue management support." Technology of technosphere safety 89 (2020): 53–64. http://dx.doi.org/10.25257/tts.2020.3.89.53-64.

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Introduction. The efficiency of search and rescue operations (PSR) due to the elimination of emergencies and fires indicates the need to create a structure for an automated control system (ACS) for technological decision-making processes at natural and industrial sites in Vietnam based on a software and hardware complex (PAC) for conducting the PSR in the Socialist Republic of Vietnam (SRV). The relevance of the research is due to the need to implement modern models and algorithms for automating the management support of the PSR and the development of automated control systems for technological processes of management decision-making at natural and industrial sites in Vietnam based on the PAC management system. Goals and objectives. The aim of the work is to reduce the response time of search and rescue units using models and algorithms to support the management of search and rescue operations using an automated control system for natural objects and industrial facilities in Vietnam based on a software and hardware complex. The practicality of the work is that the use of the recommended mathematical models, algorithms and the development of an automated system for the management of technological decision-making processes in natural and industrial sites in Vietnam, based on the software and hardware set for search and rescue operations reduce the time spent in the process. Methods. Systems analysis, statistical analysis, mathematical statistics, etc., are used to solve the problems of the study. Results and discussion thereof. The results are represented by the developed models and algorithms for supporting the management of the PSR using automated control systems at natural and industrial sites in Vietnam based on the PAC for the PSR. Conclusions. The functional structure of the automated control system for technological processes of management decision-making at natural and industrial sites in Vietnam based on a software and hardware complex for search and rescue operations, which allows you to visualize the location of victims in open areas in conditions of smoke, fog, rain. Key words: models, algorithms, automation, control support, search and rescue.
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Kalganova, N. V. "Mathematical models of optimal management of material support of educational and scientific activities of industrial universities." Herald of the Ural State University of Railway Transport, no. 4 (2020): 79–90. http://dx.doi.org/10.20291/2079-0392-2020-4-79-90.

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The paper considers mathematical differential models for managing the achievement of planned values of material support for educational and scientific activities of the university based on the analysis of this area of activity of transport universities. Models contain a mathematical description of the material and financial processes under study, which analytically show their dynamics for a certain period. The models are quite simple and can be used for planning and forecasting the financial support strategy of higher education institutions. In her research, the author relied on the work of Russian scientists, in particular, on [1-5]. This paper presents a mathematical description of the set of possible options for the system, predicting the consequences of the implemented options, and justifying the rational choice of management to achieve optimal educational and material support of the university. In this paper, we used methods for solving and investigating differential equations, as well as the MathCAD 15 software package for their numerical solution [6-8].
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Fechete, Flavia, and Anișor Nedelcu. "Modeling the Economic Performance of Industrial Systems Using Mathematical Programming." Applied Mechanics and Materials 809-810 (November 2015): 1553–58. http://dx.doi.org/10.4028/www.scientific.net/amm.809-810.1553.

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Mathematical programming models and especially their subclass - linear programming models - plays an extremely important role, both in theory and in economic practice. Linear programming, through its results, brought a considerable contribution to improving management methods in economics and it has boosted theoretical research in modeling complex economic systems, study and interpretation of laws and economic processes. Developing and designing a model for achieving the economic performance of the industrial system allows managers making optimal decision and ensures the improvement of their activity. This paper aim is to determine an optimal manufacturing program for an industrial system, so that, by its implementation, to achieve economic performance. The manufacturing program conducted using a computer software will allow this entity to optimize their management decision process by providing information related to physical production that must be executed on each of their the products, or about the unused or overloaded capacity, in order to maximize their profits.
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Cortés Pellicer, Pascual, and Faustino Alarcón Valero. "Identification of reverse logistics decision types from mathematical models." Journal of Industrial Engineering and Management 11, no. 2 (April 6, 2018): 239. http://dx.doi.org/10.3926/jiem.2530.

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Purpose: The increase in social awareness, politics and environmental regulation, the scarcity of raw materials and the desired “green” image, are some of the reasons that lead companies to decide for implement processes of Reverse Logistics (RL). At the time when incorporate new RL processes as key business processes, new and important decisions need to be made. Identification and knowledge of these decisions, including the information available and the implications for the company or supply chain, will be fundamental for decision-makers to achieve the best results. In the present work, the main types of RL decisions are identified.Design/methodology/approach: This paper is based on the analysis of mathematical models designed as tools to aid decision making in the field of RL. Once the types of interest work to be analyzed are defined, those studies that really deal about the object of study are searched and analyzed. The decision variables that are taken at work are identified and grouped according to the type of decision and, finally, are showed the main types of decisions used in mathematical models developed in the field of RL. Findings: The principal conclusion of the research is that the most commonly addressed decisions with mathematical models in the field of RL are those related to the network’s configuration, followed by tactical/operative decisions such as the selections of product’s treatments to realize and the policy of returns or prices, among other decisions.Originality/value: The identification of the main decisions types of the reverse logistics will allow the managers of these processes to know and understand them better, while offer an integrated vision of them, favoring the achievement of better results.
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Dissertations / Theses on the topic "Industrial management Australia Mathematical models"

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Powell, Robert. "Industry value at risk in Australia." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2007. https://ro.ecu.edu.au/theses/297.

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Value at Risk (VaR) models have gained increasing momentum in recent years. Market VaR is an important issue for banks since its adoption as a primary risk metric in the Basel Accords and the requirement that it is calculated on a daily basis. Credit risk modelling has become increasingly important to banks since the advent of Basel 11 which allows banks with sophisticated modelling techniques to use internal models for the purpose of calculating capital requirements. A high level of credit risk is often the key reason behind banks failing or experiencing severe difficulty. Conditional Value at Risk (CVaR) measures extreme risk, and is gaining popularity with the recognition that high losses are often impacted by a small number of extreme events.
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梁慧敏 and Wai-man Wanthy Leung. "Evolutionary optimisation of industrial systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B30252994.

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Terciyanli, Erman. "Alternative Mathematical Models For Revenue Management Problems." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/12610711/index.pdf.

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In this study, the seat inventory control problem is considered for airline networks from the perspective of a risk-averse decision maker. In the revenue management literature, it is generally assumed that the decision makers are risk-neutral. Therefore, the expected revenue is maximized without taking the variability or any other risk factor into account. On the other hand, risk-sensitive approach provides us with more information about the behavior of the revenue. The risk measure we consider in this study is the probability that revenue is less than a predetermined threshold level. In the risk-neutral cases, while the expected revenue is maximized, the probability of revenue being less than such a predetermined level might be high. We propose three mathematical models to incorporate the risk measure under consideration. The optimal allocations obtained by these models are numerically evaluated in simulation studies for example problems. Expected revenue, coefficient of variation, load factor and probability of the poor performance are the performance measures in the simulation studies. According to the results of these simulations, it shown that the proposed models can decrease the variability of the revenue considerably. In other words, the probability of revenue being less than the threshold level is decreased. Moreover, expected revenue can be increased in some scenarios by using the proposed models. The approach considered in this thesis is especially proposed for small scale airlines because risk of obtaining revenue less than the threshold level is more for this type of airlines as compared to large scale airlines.
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Cooper, William L. "Revenue management, auctions, and perishable inventories." Diss., Georgia Institute of Technology, 1999. http://hdl.handle.net/1853/25805.

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Kwok, Ho King Calvin Actuarial Studies Australian School of Business UNSW. "Energy price modelling and risk management." Awarded by:University of New South Wales. Actuarial Studies, 2007. http://handle.unsw.edu.au/1959.4/40602.

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This thesis focuses on the development of a forecasting model for short- to medium-term electricity spot prices, based on modelling the dynamics of the supply and demand functions. It is found that the equilibrium assumption frequently adopted in electricity price models does not always hold; to overcome this problem, a notional demand process derived from the market clearing condition is proposed. Not only is this demand process able to capture all the price-affecting factors in one variable, but it also allows the equilibrium assumption to be satisfied and a spot price model to be built, using any appropriate form of hypothetical supply function. In addition, this thesis presents a model for approximating and modelling the bid stacks by capturing the points that govern their shape and location. Integrating these two models provides a realistic model that has a mean absolute percentage error of approximately 19% and 24% for week- and month-ahead forecasts respectively, when applied to the New South Wales (NSW) half-hourly electricity spot prices. Additionally, the density forecasting evaluation method proposed by Diebold et al. (1998) is employed in the thesis to assess the performance of the model. Besides the development of a spot price model, a two-part empirical study is made of the prices of NSW electricity futures contracts. The first part of the study develops a method based on the principle of certainty equivalence, which enables the market utility function to be recovered from a set of futures market quotes. The method is tested with two different sets of simulated data and works as expected. However, it is unable to obtain useful results from the NSW market quotes due to the poor data quality. The second part uses a regression method to investigate the relationship between futures prices and the descriptive statistics of the underlying spot prices. The result suggests that futures prices in NSW are linear combinations of the median and volatility of the final payoff.
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Ertek, Gurdal. "Pricing models for two-stage supply chains." Diss., Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/30693.

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Su, Wei, and 蘇薇. "Partner selection and production-distribution planning for the design of optimal supply chain networks." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B41757853.

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Soucik, Victor. "Finding the true performance of Australian managed funds." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2002. https://ro.ecu.edu.au/theses/730.

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When making conclusions about the performance of managed funds, it is critical that the framework in which such performance is measured provides an accurate and unbiased environment. In this thesis I search for true performance of the two major classes of funds- equity as well as fixed interest managed funds. Focusing, first on the former class, I examine five measurement models across three risk-free proxies, nine benchmarks proposed by the extant literature (covering conditional and unconditional as well as single and multi factor definitions) and over three independent periods in an effort to identity (in a consistent setting) the most accurate and least biast methodology. I also use the Australian dataset, which inherently mitigates any data biases that may potentially afflict US studies of these methodologies, since these were developed from the same dataset on which they were later tested. Not finding a pre-existing benchmark that is objective yet informative, I develop an independent model that satisfies these, sourcing from fifteen factor candidates across four categories. I find that teaming up a fund based market factor with well-defined proxies for size, value, momentum and conditional dividend yield provides the optimal benchmark. The latter class comprising fixed-interest managed funds is a segment left largely unexplored in the financial literature and neglected outright in the Australian context. I examine three risk-free proxies, six benchmark classes encompassing twenty-one potential factors, across five models and two independent time frames in an effort to establish the most informative and least biased setting. The task is complicated by two issues - an acute lack of Australian data (demanding additional bootstrap simulations and bridging tests with the US markets) and the need for a two-pass (time-series and cross-sectional) analysis, arising from the different information content benchmarks carry in these two dimensions. My results, consistent across time, show that a correct combination of a bond market variable, a mixture of interest rate factors and economic factors as well as the proxy for movements in the equity markets yield the optimal benchmark. Both fund classes point to Jensen's Alpha as the preferred model, but Treynor and Mazuy's definition of a quadratic measure is adequate if timing-selectivity separation is required. Neither class is significantly sensitive to the choice of risk free proxy featuring in the performance measures.
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Xu, Yihua, and 許意華. "Procurement risk management using commodity futures: a multistage stochastic programming approach." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B37823413.

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Xu, Suxiu, and 徐素秀. "Truthful, efficient auctions for transportation procurement." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/206443.

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Transportation procurement problem (TPP) is the problem of setting transportation service prices, delivery timing and quantity, and controlling costs and capacity to reduce empty movements and improve market efficiency. The purchase of transportation service is traditionally achieved using a request for proposal and long-term contracts. However, as business relationships become ever more flexible and dynamic, there has been an increasing need to hedge the risks of traditional transportation procurement such as entrance of new carriers and sudden drop in fuel price. This thesis proposes a holistic aution-based solution for the TPP. Four typical scenarios are investigated. The first scenario incorporates bilateral bidding into auction mechanism design for multi-unit TPP. This scenario considers one-sided Vickrey-Clarke-Groves (O-VCG) combinatorial auctions for a complex transportation marketplace with multiple lanes. This scenario then designs three alternative multi-unit trade reduction (MTR) mechanisms for the bilateral exchange transportation marketplace where all the lanes are partitioned into distinct markets. Proposed mechanisms ensure incentive compatibility, individual rationality, budget balance and asymptotical efficiency. The second scenario presents a double auction model for the TPP in a dynamic single-lane transportation environment. This scenario first addresses the TPP in a transportation spot market with stochastic but balanced or “symmetric” demand and supply. A periodic sealed double auction (PSDA) is proposed. This scenario then devises a modified PSDA (M-PSDA) to address the TPP with “asymmetric” demand and supply. The auctioneer is likely to gain higher profits from setting a relatively short auction length. However, it is optimal to run the auction (either PSDA or MPSDA) with a relatively large auction length, when maximizing either the social welfare or the utility of shippers and carriers (agents). When the degree of supply-demand imbalance is low, the auctioneer’s myopic optimal expected profit under supply-demand imbalance is larger than that under symmetric demand and supply. This third scenario presents an auction-based model for the TPP in make-toorder systems. The optimality of dynamic base-stock type (S(x)-like policy) is established. The optimal allocation can be achieved by running an O-VCG auction or a first-price auction with closed-form reserve prices. By mild technical modifications, the results derived in the infinite horizon case can all be extended to the finite horizon case. The fourth scenario proposes allocatively efficient auction mechanisms for the distributed transportation procurement problem (DTPP), which is generally the problem of matching demands and supplies over a transportation network. This scenario constructs an O-VCG combinatorial auction for the DTPP where carriers are allowed to bid on bundles of lanes. To simplify the execution of auction, this scenario next proposes a primal-dual Vickrey (PDV) auction based on insights from the known Ausubel auctions and the primal-dual algorithm. The PDV auction realizes VCG payments and truthful bidding under the condition of seller-submodularity, which implies that the effect of each individual carrier is decreasing when the coalition increases.
published_or_final_version
Industrial and Manufacturing Systems Engineering
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Doctor of Philosophy
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Books on the topic "Industrial management Australia Mathematical models"

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A, Ciriani Tito, ed. Operational research in industry. Houndmills, Basingstoke, Hampshire: Macmillan Press, 1999.

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A, Ottjes Jaap, and Lodewijks Gabriël, eds. The Delft systems approach: Analysis and design of industrial systems. London: Springer, 2008.

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Brandon-Jones, Alistair. Quantitative analysis in operations management. New York: Financial Times Prentice Hall, 2008.

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Afuah, Allan. Business models: A strategic management approach. New York: McGraw-Hill/Irwin, 2004.

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Ziębik, Andrzej. Mathematical modelling of energy management systems in industrial plants. Wrocław: Zakład Narodowy Imienia Ossolińskich Wydawn. Polskiej Akademii Nauk, 1990.

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Gordon, Ferrier, ed. Quantitative methods. Exeter: Crucial, 2002.

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August-Wilhelm, Scheer, ed. Prozessorientierte Unternehmensmodellierung. Wiesbaden: Gabler, 1994.

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Bloom, Nick. Measuring and explaining management practices across firms and countries. Cambridge, Mass: National Bureau of Economic Research, 2006.

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Bloom, Nick. Measuring and explaining management practices across firms and countries. London: Centre for Economic Performance, London School of Economics and Political Science, 2006.

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Waters, C. D. J. Quantitative methods for business. 5th ed. Harlow, England: Financial Times Prentice Hall, 2011.

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Book chapters on the topic "Industrial management Australia Mathematical models"

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Tan, Raymond R., Kathleen B. Aviso, Michael Angelo B. Promentilla, Krista Danielle S. Yu, and Joost R. Santos. "Mathematical Foundations of Input–Output Models." In Lecture Notes in Management and Industrial Engineering, 9–28. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1873-3_2.

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Parra, E. "Optimal Tax Planning with Mathematical Programming Models." In Lecture Notes in Management and Industrial Engineering, 257–64. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-96005-0_32.

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Yaylali, Emine, and Zikriye Melisa Erdogan. "Mathematical Models of HIV: Methodologies and Applications." In Lecture Notes in Management and Industrial Engineering, 345–59. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42416-9_31.

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Kyratsis, Panagiotis, Cesar Garcia-Hernandez, Dimitrios Vakondios, and Aristomenis Antoniadis. "Thrust Force and Torque Mathematical Models in Drilling of Al7075 Using the Response Surface Methodology." In Management and Industrial Engineering, 151–64. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23838-8_6.

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Mutanov, Galimkair. "Methodology for Identification of Competitive Industrial Clusters." In Mathematical Methods and Models in Economic Planning, Management and Budgeting, 327–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-45142-7_9.

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Rius-Sorolla, G., J. Maheut, S. Estelles-Miguel, and J. P. García-Sabater. "Review of Symmetry-Breaking Options on Mathematical Programming Models with Rolling Horizons Procedure." In Lecture Notes in Management and Industrial Engineering, 71–77. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67708-4_8.

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Potriasaev, Semyon, Viacheslav Zelentsov, and Ilya Pimanov. "Computational Processes Management Methods and Models in Industrial Internet of Things." In Computational Statistics and Mathematical Modeling Methods in Intelligent Systems, 266–77. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31362-3_26.

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Bazan, Ehab, and Mohamad Y. Jaber. "The Development and Analysis of Environmentally Responsible Supply Chain Models." In Operations and Service Management, 1294–317. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3909-4.ch058.

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Inventory management and supply chain management are integral issues and prime areas of concern in production and operations management, and industrial engineering. There is a drive for businesses and organizations to be accountable for their environmental impacts. Guaranteeing environmentally conscious supply chain operations is strongly linked to an organization's sustainability and overall success. The responsible management of forward and return product flows in production and inventory environments is a rapidly increasing requirement. This can be attributed to economic, environmental and/ or regulatory motivations. Mathematical modeling of such systems assists decision-making processes and provided a better understanding of the behavior of such production and inventory environments.
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Bazan, Ehab, and Mohamad Y. Jaber. "The Development and Analysis of Environmentally Responsible Supply Chain Models." In Green Supply Chain Management for Sustainable Business Practice, 52–82. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-0635-5.ch003.

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Inventory management and supply chain management are integral issues and prime areas of concern in production and operations management, and industrial engineering. There is a drive for businesses and organizations to be accountable for their environmental impacts. Guaranteeing environmentally conscious supply chain operations is strongly linked to an organization's sustainability and overall success. The responsible management of forward and return product flows in production and inventory environments is a rapidly increasing requirement. This can be attributed to economic, environmental and/ or regulatory motivations. Mathematical modeling of such systems assists decision-making processes and provided a better understanding of the behavior of such production and inventory environments.
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Arredondo-Soto, Karina Cecilia, Marco A. Miranda-Ackerman, and Mydory Oyuky Nakasima-López. "Supply Chain for Remanufacturing Operations." In Handbook of Research on Industrial Applications for Improved Supply Chain Performance, 73–100. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-0202-0.ch004.

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Remanufacturing requires new skills in forecasting, planning, inventory management, and many other supply chain practices. The main complicating characteristics of remanufacturing were identified in 2000. In 2011, the evolution in the solution of these complications from 2000 to 2009 was identified, but more practical research was needed. The tools developed during that period were mostly quantitative, based on mathematical models and simulation but not associated with any kind of specific remanufacturing operation. For this reason, this chapter analyzes practical research developed from 2010 to 2019 by including tools methods and techniques related to supply chain for remanufacturing operations. The contribution of this literature review is to determine the trends developed in the last 10 years to mitigate the effects of the complications generated by the remanufacturing operations. As an added value, the cases of studies that include applications to specific remanufactured products is highlighted.
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Conference papers on the topic "Industrial management Australia Mathematical models"

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Ryzhkova, А. V., and N. A. Zhilnikova. "METHODS FOR ECO-EFFICIENCY ASSESSMENT OF ORGANIZATIONS." In MODELING AND SITUATIONAL MANAGEMENT THE QUALITY OF COMPLEX SYSTEMS. Saint Petersburg State University of Aerospace Instrumentation, 2021. http://dx.doi.org/10.31799/978-5-8088-1558-2-2021-2-150-156.

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This article discusses the modern concept of eco-efficiency, based on the methods of using resources for the development of an organization in terms of economic and environmental indicators through more efficient use of resources and reducing pollution. Its differences from the traditional principles of environmental efficiency are determined. Mathematical models for assessing the eco-efficiency of industrial production are proposed. The applicability of the developments is shown on the example of a microelectronics enterprise. The presented models make it possible to measure the eco-efficiency indicator, taking into account the use of all eco-parameters affecting the change in the efficient use of resources and reducing the level of pollution.
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Jiang, Bo, Amro M. Farid, and Kamal Youcef-Toumi. "Impacts of Industrial Baseline Errors on Costs and Social Welfare in the Demand Side Management of Day-Ahead Wholesale Markets." In ASME 2015 9th International Conference on Energy Sustainability collocated with the ASME 2015 Power Conference, the ASME 2015 13th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2015 Nuclear Forum. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/es2015-49459.

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Demand Side Management (DSM) has been recognized for its potential to counteract the intermittent nature of renewable energy, increase system efficiency, and reduce system costs. While the popular approach among academia adopts a social welfare maximization formulation, the industrial practice in the United States electricity market compensates customers according to their load reduction from a predefined electricity consumption baseline that would have occurred without DSM. This paper is an extension of a previous paper studying the differences between the industrial & academic approach to dispatching demands. In the previous paper, the comparison of the two models showed that while the social welfare model uses a stochastic net load composed of two terms, the industrial DSM model uses a stochastic net load composed of three terms including the additional baseline term. That work showed that the academic and industrial optimization method have the same dispatch result in the absence of baseline errors given the proper reconciliation of their respective cost functions. DSM participants, however, and very much unfortunately, are likely to manipulate the baseline in order to receive greater financial compensation. This paper now seeks to study the impacts of erroneous industrial baselines in a day-ahead wholesale market context. Using the same system configuration and mathematical formalism, the industrial model is compared to the social welfare model. The erroneous baseline is shown to result in a different and more importantly costlier dispatch. It is also likely to require more control activity in subsequent layers of enterprise control. Thus an erroneous baseline is likely to increase system costs and overestimate the potential for social welfare improvements.
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Sivanuja, T., and YG Sandanayake. "Industry 4.0 enabled predictive maintenance of facilities: A study on applicability, benefits and challenges." In 10th World Construction Symposium. Building Economics and Management Research Unit (BEMRU), University of Moratuwa, 2022. http://dx.doi.org/10.31705/wcs.2022.47.

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Maintenance management is an important function under Facilities Management (FM). Industries moved to preventive maintenance models to counteract the inefficiencies of reactive maintenance and further evolved into predictive maintenance (PdM) models. The demand for Industry 4.0 enabled PdM for FM has risen as a result of the industrial revolution and the dynamic nature of the FM functions. Thus, the study aimed to investigate the applicability, benefits, and challenges of applying Industry 4.0 concept for effective PdM in FM. The qualitative research approach was undertaken to accomplish the aim. A comprehensive literature review followed by 15 semi-structured interviews was carried out with experts in the maintenance sector who have Industry 4.0 knowledge. The data was collected from experts in Australia, Qatar, Dubai, Singapore, and Sri Lanka, and analysed through code-based content analysis using NVivo 12. The results demonstrate that there is a huge potential for using Industry 4.0 smart technologies such as big data analytics, Cyber-Physical Systems (CPS), autonomous robots, Cloud Computing, Industrial Internet of Things (IIoT), cybersecurity, Machine Learning (ML), Augmented Reality (AR), Data Mining (DM), system integration, and simulation for PdM under FM. Applying Industry 4.0 concept for effective PdM under FM provides significant benefits such as the deployment of a zero-failure strategy, establishment of machine-to-machine communication and interaction, detection of early anomalies and extended equipment lifetime. Lack of technological knowledge, capital, data management, employees’ interest, integration between systems, standardized procedures, and internet access are identified key challenges.
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Talero-Sarmiento, Leonardo Hernán, Julián A. Durán-Peña, Kevin A. Salcedo-Rugeles, and Sergio M. Garcia-Franco. "The identification of improvement strategies in continuous assessment using sentiment analysis in the Operational Research course." In INNODOCT 2019. Valencia: Universitat Politècnica de València, 2019. http://dx.doi.org/10.4995/inn2019.2019.10246.

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The University aims is to graduate professionals with high levels of competence to impact society positively. In consequence, the institutions apply different educational strategies to focus on improving the curricular competences until mastery the whole competences topics. An alternative highly applied is continuous assessment, which is a form of educational examination that evaluates the progress of a student throughout a prescribed course. A critical course in the engineer formation is Operational Research; this course focuses on scientific management supported by mathematical models such as decision theory, stochastic scenarios, simulation, mathematical optimization etcetera. This work aim is to diagnose the continuous assessment strategy apply to Industrial and System engineer students enrolled in Operational Research course, to do that, this research carries out a sentiment analysis which is a text classification tool that analyses an incoming message (in this case a perception essay) and indicates whether the underlying sentiment is positive, negative or neutral. Furthermore, the Techniques applied to group the emotions of anger, anticipations, disgust, fear, joy, negative, positive, sadness, surprise, and trust. Taking into account the initial results, the authors highlight alternatives such as the flipped classroom, gamification as educational strategies to implement in futures courses looking to improving the continuous assessment positive perception.
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Di Francesco, Domenic, Marios Chryssanthopoulos, Michael Havbro Faber, and Ujjwal Bharadwaj. "Bayesian Multi-Level Modelling for Improved Prediction of Corrosion Growth Rate." In ASME 2020 39th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/omae2020-18744.

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Abstract In pipelines, pressure vessels and various other steel structures, the remaining thickness of a corroding ligament can be measured directly and repeatedly over time. Statistical analysis of these measurements is a common approach for estimating the rate of corrosion growth, where the uncertainties associated with the inspection activity are taken into account. An additional source of variability in such calculations is the epistemic uncertainty associated with the limited number of measurements that are available to engineers at any point in time. Traditional methods face challenges in fitting models to limited or missing datasets. In such cases, deterministic upper bound values, as recommended in industrial guidance, are sometimes assumed for the purpose of integrity management planning. In this paper, Bayesian inference is proposed as a means for representing available information in consistency with evidence. This, in turn, facilitates decision support in the context of risk-informed integrity management. Aggregating inspection data from multiple locations does not account for the possible variability between the locations, and creating fully independent models can result in excessive levels of uncertainty at locations with limited data. Engineers intuitively acknowledge that the areas with more sites of corrosion should, to some extent, inform estimates of growth rates in other locations. Bayesian multi-level (hierarchical) models provide a mathematical basis for achieving this by means of the appropriate pooling of information, based on the homogeneity of the data. Included in this paper is an outline of the process of fitting a Bayesian multi-level model and a discussion of the benefits and challenges of pooling inspection data between distinct locations, using example calculations and simulated data.
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Perera, Lokukaluge P., and Brage Mo. "Data Analytics for Capturing Marine Engine Operating Regions for Ship Performance Monitoring." In ASME 2016 35th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/omae2016-54168.

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This study proposes marine engine centered data analytics as a part of the ship energy efficiency management plan (SEEMP) to overcome the current shipping industrial challenges. The SEEMP enforces various emission control measures, where ship energy efficiency should be evaluated by collecting vessel performance and navigation data. That information is used to develop the proposed data analytics that are implemented on the engine-propeller combinator diagram (i.e. one propeller shaft with its own direct drive main engine). Three marine engine operating regions from the initial data analysis are noted under the combinator diagram and the proposed data analytics (i.e. data clustering methodology) to capture the shape of these regions are implemented. That consists of implementing the Gaussian Mixture Models (GMMs) to classify the most frequent operating regions of the marine engine. Furthermore, the Expectation Maximization (EM) algorithm is used to calculate the respective parameters of the GMMs. This approach can also be seen as a data clustering algorithm that facilitated by an iterative process for capturing each operating region of the marine engine (i.e. the combinatory diagram) with the respective mean and covariance values. Hence, these data analytics can be used in the SEEMP to monitor the performance of a vessel with respect to the marine operating regions. Furthermore, it is expected to develop advanced mathematical models of ship performance monitoring under these operational regions of the marine engine as the future work.
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