Robust optimization for U-shaped assembly line worker assignment and balancing problem with uncertain task times

Awareness of the importance of U-shaped assembly line balancing problems is all on the rise. In the U-shaped assembly line, balancing is affected by the uncertainty associated with the assembly task times. Therefore, it is crucial to develop an approach to respond to the uncertainty caused by the task times. When the great majority of existing literature related to uncertainty in the assembly line is considered, it is observed that the U-shaped assembly line balancing problem under uncertainty is scarcely investigated. That being the case, we aim to fill this research gap by proposing a robust counterpart formulation for the addressed problem. In this study, a robust optimization model is developed for the U-shaped assembly line worker assignment and balancing problem (UALWABP) to cope with the task time uncertainty characterized by a combined interval and polyhedral uncertainty set. A real case study is conducted through data from a company producing water meters

Experimental assessment of the productivity improvement when using U-shaped production cells with variable takt time

International audiencePurpose – The aims of this research is to discuss the benefits of U layout for production cell operating in variable takt time. Different experiments were conducted using benchmarks, in order to highlight the performance gap between a straight cell and a U-cell. Design/methodology/approach – The implementation of the production cell, in U-shaped or in straight line, is optimized through linear programming based on the number of operators. The two corresponding programs, in Mosel language, use the same approach, in order to not introduce defects in the comparison of results. The study used our own datasets and well known academic benchmarks. Findings – A comparison between the obtained takt times, with equivalent operating conditions, in U-cell and straight cell was conducted. A significant increase of the production rate was observed. This increase has often exceeded 10 per cent to reach 32 per cent. All the experiments show that, with the same number of operators, a cell in a U layout is always at least as efficient, in terms of reachable production rates, than an equivalent cell in a linear layout. 96 per cent give an improvement of production rate. Moreover, the dispersion of the U-cell results is weaker, which suggests that the U-layout gives, in more robust manner, better performances.Research limitations/implications – The results were obtained through a study of various academic benchmarks. The results must be validated on industrial situations.Practical implications – This paper will be very useful for researchers and practitioners in order to understand lean implementations and its derived benefits. This paper will allow them evaluating and analysing the expected benefits of the implementation of the production cell in U-shaped (operating in variable takt time).Originality/value – U-Cells constitute an appropriate solution for a layout of any kind of production cells with variable structure. When facing a significant variation in the demand, the response consists in modulating the number of operators assigned to the cell. This study addresses jointly the problem of U-cells layout and the operation in variable takt time

Stability measure for a generalized assembly line balancing problem

AbstractA generalized formulation for assembly line balancing problem (GALBP) is considered, where several workplaces are associated with each workstation. Thus, all tasks assigned to the same workstation have to be partitioned into blocks: each block regroups all tasks to be performed at the same workplace. The product items visit all workplaces sequentially, therefore, all blocks are proceeded in a sequential way. However, the tasks grouped into the same block are executed simultaneously. As a consequence, the execution of a block takes only the time of its longest task. This parallel execution modifies the manner to take into account the cycle time constraint. Precedence and exclusion constraints also exist for workstations and their workplaces. The objective is to assign all given tasks to workstations and workplaces while minimizing the line cost estimated as a weighted sum of the number of workstations and workplaces. The goal of this article is to propose a stability measure for feasible and optimal solutions of this problem with regard to possible variations of the processing time of certain tasks. A heuristic procedure providing a compromise between the objective function and the suggested stability measure is developed and evaluated on benchmark data sets

Satisficing data envelopment analysis: a Bayesian approach for peer mining in the banking sector

YesOver the past few decades, the banking sectors in Latin America have undergone rapid structural changes to improve the efficiency and resilience of their financial systems. The up-to-date literature shows that all the research studies conducted to analyze the above-mentioned efficiency are based on a deterministic data envelopment analysis (DEA) model or econometric frontier approach. Nevertheless, the deterministic DEA model suffers from a possible lack of statistical power, especially in a small sample. As such, the current research paper develops the technique of satisficing DEA to examine the still less explored case of Peru. We propose a Satisficing DEA model applied to 14 banks operating in Peru to evaluate the bank-level efficiency under a stochastic environment, which is free from any theoretical distributional assumption. The proposed model does not only report the bank efficiency, but also proposes a new framework for peer mining based on the Bayesian analysis and potential improvements with the bias-corrected and accelerated confidence interval. Our study is the first of its kind in the literature to perform a peer analysis based on a probabilistic approach

Equilibrado de líneas de montaje de productos voluminosos

Preprin

Optimization Models for Sustainable Design and Management of Biopower Supply Chains

This dissertation presents optimization models to aid with the sustainable design and management of biopower (biomass cofiring) supply chains. We address three main challenges associated with today’s biopower projects: i) high cost of biomass collection, storage and delivery, ii) inefficiency of the mechanisms used to incentivize biomass usage for generating electricity, and iii) lack of clear understanding about the trade-offs between economic and environmental impacts of biopower supply chains. In order to address the high cost of delivering biomass, we present a novel mixed integer nonlinear program that integrates production and transportation decisions at power plants. Proposed model captures the loss in process efficiencies from using biomass, in-vestment and operational costs associated with cofiring, and savings due to production tax credit (PTC), a major governmental incentive to support biopower. We develop a La-grangian relaxation approach to provide upper bounds, and two linear approximations to provide lower bounds for the problem. An important finding is that the one-size-fits-all approach of PTC is not effective in motivating plants to utilize biomass and there is a need for sophisticated incentive schemes. In order to address the second issue, we propose alter-natives for the existing PTC incentive. The proposed flexible alternatives are functions of plant capacity and biomass cofiring ratio. We use a resource allocation framework to model and analyze the profit-earning potentials and fairness of the proposed incentive schemes. Finally, in order to address the last challenge, we propose a stochastic biobjective optimiza-tion model to analyze the economic and environmental impacts of biopower supply chains. The economic objective function maximizes the potential profits in the supply chain and the environmental objective function minimizes the life cycle greenhouse gasses (GHG). We use a life cycle assessment (LCA) approach to derive the emission factors for this objective function. We capture uncertainties of biomass quality and supply via the use of chance constraints. The results of this dissertation work are useful for electric utility companies and policy makers. Utility companies can use the proposed models to identify ways to improve biopower production, have better environmental performance, and make use of the existing incentives. Policy makers would gain insights on designing incentive schemes for a more efficient utilization of biomass and a fairer distribution of tax-payers money

Conception de lignes de fabrication sous incertitudes (analyse de sensibilité et approche robuste.)

Les travaux présentés dans cette thèse portent sur la conception de systèmes de fabrication en contexte incertain. La conception d un tel système peut être vue comme un problème d optimisation qui consiste à trouver une configuration qui permet d optimiser certains objectifs tout en respectant des contraintes technologiques et économiques connues. Les systèmes de fabrication étudiés dans ce mémoire sont des lignes d assemblage et d usinage. La première est une ligne qui se présente comme une chaîne de postes de travail où, dans chaque poste, les opérations d assemblage s exécutent de manière séquentielle. La deuxième, quant à elle, est une ligne particulière qui se compose de machines de transfert comportant plusieurs boîtiers multibroches où les opérations s exécutent simultanément. Dans un premier temps, nous décrivons de différentes approches permettant de modéliser l incertitude des données en optimisation. Une attention particulière est portée sur les deux approches suivantes : l approche robuste et l analyse de sensibilité. Puis, nous présentons trois applications : la conception d une ligne d assemblage et d une ligne d usinage soumises aux variations de temps opératoires et la conception d une ligne d assemblage avec les temps opératoires connus sous la forme d intervalles des valeurs possibles. Pour chaque application, nous identifions les performances attendues ainsi que la complexité de la prise en compte de l incertitude. Ensuite, nous proposons de nouveaux critères d optimisation en adéquation avec la problématique introduite. Enfin des méthodes de résolution sont développées pour appréhender les différents problèmes mis en évidence par ces critères.The presented work deals with the design of production systems in uncertain context. The design of such systems can be interpreted as an optimization problem that consists to find a configuration optimizing certain objectives and respecting technological and economical constraints. The production systems studied in this thesis are the assembly and transfer lines. The first one is the line that can be represented as a flow-oriented chain of workstations where, at each workstation, the tasks are executed in a sequential manner. The second is a particular line that is composed of transfer machines including several multi-spindle heads where the tasks are executed simultaneously. At first, we describe different approaches that permit to model the uncertainty of data in optimization. A particular attention is attracted to two following approaches: robust approach and sensitivity analysis. Then, we present three applications: the design of assembly and transfer lines under variations of task processing times and the design of an assembly line with interval task processing times. For each application, we identify the expected performances as well as the complexity of taking into account the uncertainty. Thereafter, we propose some new optimization criteria in adequacy with the introduced problematic. Finally, resolution methods are developed to solve different problems engendered by these criteria.ST ETIENNE-ENS des Mines (422182304) / SudocSudocFranceF

Design and Management of Manufacturing Systems

Although the design and management of manufacturing systems have been explored in the literature for many years now, they still remain topical problems in the current scientific research. The changing market trends, globalization, the constant pressure to reduce production costs, and technical and technological progress make it necessary to search for new manufacturing methods and ways of organizing them, and to modify manufacturing system design paradigms. This book presents current research in different areas connected with the design and management of manufacturing systems and covers such subject areas as: methods supporting the design of manufacturing systems, methods of improving maintenance processes in companies, the design and improvement of manufacturing processes, the control of production processes in modern manufacturing systems production methods and techniques used in modern manufacturing systems and environmental aspects of production and their impact on the design and management of manufacturing systems. The wide range of research findings reported in this book confirms that the design of manufacturing systems is a complex problem and that the achievement of goals set for modern manufacturing systems requires interdisciplinary knowledge and the simultaneous design of the product, process and system, as well as the knowledge of modern manufacturing and organizational methods and techniques