A mixed-integer programming model for cycle time minimization in assembly line balancing: Using rework stations for performing parallel tasks

[EN] In assembly lines, rework stations are generally used for reprocessing defective items. On the other hand, using rework stations for this purpose only might cause inefficient usage of the resources in this station especially in an assembly line with a low defective rate. In this study, a mixed-integer programming model for cycle time minimization is proposed by considering the use of rework stations for performing parallel tasks. By linearizing the non-linear constraint about parallel tasks using a variate transformation, the model is transformed to a linear-mixed-integer form. In addition to different defective rates, different rework station positions are also considered using the proposed model. The performance of the model is analyzed on several test problems from the related literature.Cavdur, F.; Kaymaz, E. (2020). A mixed-integer programming model for cycle time minimization in assembly line balancing: Using rework stations for performing parallel tasks. International Journal of Production Management and Engineering. 8(2):111-121. https://doi.org/10.4995/ijpme.2020.12368OJS11112182Altekin, F. T., Bayindir, Z. P., & Gümüskaya, V. (2016). Remedial actions for disassembly lines with stochastic task times. Computers & Industrial Engineering, 99, 78-96. https://doi.org/10.1016/j.cie.2016.06.027Anderson, E. J., & Ferris, M. C. (1994). Genetic algorithms for combinatorial optimization: the assemble line balancing problem. ORSA Journal on Computing, 6(2), 161-173. https://doi.org/10.1287/ijoc.6.2.161Askin, R. G., & Zhou, M. (1997). A parallel station heuristic for the mixed-model production line balancing problem. International Journal of Production Research, 35(11), 3095-3106. https://doi.org/ 10.1080/002075497194309Bard, J. F. (1989). Assembly line balancing with parallel workstations and dead time. The International Journal of Production Research, 27(6), 1005-1018. https://doi.org/10.1080/00207548908942604Bartholdi, J. J. (1993). Balancing two-sided assembly lines: a case study. International Journal of Production Research, 31(10), 2447-2461. https://doi.org/10.1080/00207549308956868Battaia, O., & Dolgui, A. (2013). A taxonomy of line balancing problems and their solution approaches. International Journal of Production Economics, 142(2), 259-277. https://doi.org/10.1016/j.ijpe.2012.10.020Baybars, I. (1986). A survey of exact algorithms for the simple assembly line balancing problem. Management science, 32(8), 909-932. https://doi.org/10.1287/mnsc.32.8.909Baykasoglu, A., & Demirkol Akyol, S. (2014). Ergonomic assembly line balancing. Journal of the Faculty of Engineering and Architecture of Gazi University, 29(4), 785-792. https://doi.org/10.17341/gummfd.00296Becker, C., & Scholl, A. (2006). A survey on problems and methods in generalized assembly line balancing. European journal of operational research, 168(3), 694-715. https://doi.org/10.1016/j.ejor.2004.07.023Boysen, N., Fliedner, M., & Scholl, A. (2007). A classification of assembly line balancing problems. European journal of operational research, 183(2), 674-693. https://doi.org/10.1016/j.ejor.2006.10.010Bryton, B. (1954). Balancing of a continuous production line. Master's Thesis, Northwestern University, Evanston.Cercioglu, H., Ozcan, U., Gokcen, H., & Toklu, B. (2009). A simulated annealing approach for parallel assembly line balancing problem. Journal of the Faculty of Engineering and Architecture of Gazi University, 24(2), 331-341.Efe, B., Kremer, G. E. O., & Kurt, M. (2018). Age and gender-based workload constraint for assembly line worker assignment and balancing problem in a textile firm. International Journal of Industrial Engineering, 25(1), 1-17.Ghosh, S., & Gagnon, R. J. (1989). A comprehensive literature review and analysis of the design, balancing and scheduling of assembly systems. The International Journal of Production Research, 27(4), 637-670. https://doi.org/10.1080/00207548908942574Gokcen, H., & Baykoc, Ö. F. (1999). A new line remedial policy for the paced lines with stochastic task times. International Journal of Production Economics, 58(2), 191-197. https://doi.org/10.1016/S0925-5273(98)00123-6Gokcen, H., Agpak, K., & Benzer, R. (2006). Balancing of parallel assembly lines. International Journal of Production Economics, 103(2), 600-609. https://doi.org/10.1016/j.ijpe.2005.12.001Guner, B., & Hasgul, S. (2012). U-Type assembly line balancing with ergonomic factors for balance stability. Journal of the Faculty of Engineering and Architecture of Gazi University, 27(2), 407-415.Kaplan, O. (2004). Assembly line balancing with task paralleling. Master's Thesis, METU, Ankara.Kara, Y., Ozguven, C., Yalcın, N., & Atasagun, Y. (2011). Balancing straight and U-shaped assembly lines with resource dependent task times. International Journal of Production Research, 49(21), 6387-6405. https://doi.org/10.1080/00207543.2010.535039Kara, Y., Atasagun, Y., Gokcen, H., Hezer, S., & Demirel, N. (2014). An integrated model to incorporate ergonomics and resource restrictions into assembly line balancing. International Journal of Computer Integrated Manufacturing, 27(11), 997-1007. https://doi.org/10.1080/0951192X.2013.874575Kazemi, S. M., Ghodsi, R., Rabbani, M., & Tavakkoli-Moghaddam, R. (2011). A novel two-stage genetic algorithm for a mixed-model U-line balancing problem with duplicated tasks. The International Journal of Advanced Manufacturing Technology, 55(9-12), 1111-1122. https://doi.org/10.1007/s00170-010-3120-6Kim, Y. K., Kim, Y., & Kim, Y. J. (2000). Two-sided assembly line balancing: a genetic algorithm approach. Production Planning & Control, 11(1), 44-53. https://doi.org/10.1080/095372800232478Kottas, J. F., & Lau, H. S. (1976). A total operating cost model for paced lines with stochastic task times. AIIE Transactions, 8(2), 234-240. https://doi.org/10.1080/05695557608975072Lau, H. S., & Shtub, A. (1987). An exploratory study on stopping a paced line when incompletions occur. IIE transactions, 19(4), 463-467. https://doi.org/10.1080/07408178708975421Lee, T. O., Kim, Y., & Kim, Y. K. (2001). Two-sided assembly line balancing to maximize work relatedness and slackness. Computers & Industrial Engineering, 40(3), 273-292. https://doi.org/10.1016/S0360-8352(01)00029-8Mutlu, O., & Ozgormus, E. (2012). A fuzzy assembly line balancing problem with physical workload constraints. International Journal of Production Research, 50(18), 5281-5291. https://doi.org/10.1080/00207543.2012.709647Ozcan, U., & Toklu, B. (2010). Balancing two-sided assembly lines with sequence-dependent setup times. International Journal of Production Research, 48(18), 5363-5383. https://doi.org/10.1080/00207540903140750Pinto, P., Dannenbring, D. G., & Khumawala, B. M. (1975). A branch and bound algorithm for assembly line balancing with paralleling. The International Journal of Production Research, 13(2), 183-196. https://doi.org/10.1080/00207547508942985Sabuncuoglu, I., Erel, E., & Alp, A. (2009). Ant colony optimization for the single model U-type assembly line balancing problem. International Journal of Production Economics, 120(2), 287-300. https://doi.org/10.1016/j.ijpe.2008.11.017Salveson, M. E. (1955). The assembly line balancing problem. The Journal of Industrial Engineering, 18-25.Scholl, A., & Becker, C. (2006). State-of-the-art exact and heuristic solution procedures for simple assembly line balancing. European Journal of Operational Research, 168(3), 666-693. https://doi.org/10.1016/j.ejor.2004.07.022Shtub, A. (1984). The effect of incompletion cost on line balancing with multiple manning of work stations. The International Journal of Production Research, 22(2), 235-245. https://doi.org/10.1080/00207548408942450Silverman, F. N., & Carter, J. C. (1986). A cost-based methodology for stochastic line balancing with intermittent line stoppages. Management Science, 32(4), 455-463. https://doi.org/10.1287/mnsc.32.4.455Simaria, A. S., & Vilarinho, P. M. (2001). The simple assembly line balancing problem with parallel workstations-a simulated annealing approach. Int J Ind Eng-Theory, 8(3), 230-240.Sivasankaran, P., & Shahabudeen, P. (2014). Literature review of assembly line balancing problems. The International Journal of Advanced Manufacturing Technology, 73(9-12), 1665-1694. https://doi.org/10.1007/s00170-014-5944-ySuer, G. A. (1998). Designing parallel assembly lines. Computers & industrial engineering, 35(3-4), 467-470. https://doi.org/10.1016/S0360-8352(98)00135-1Suwannarongsri, S., & Puangdownreong, D. (2008). Optimal assembly line balancing using tabu search with partial random permutation technique. International Journal of Management Science and Engineering Management, 3(1), 3-18. https://doi.org/10.1080/17509653.2008.10671032Tiacci, L., Saetta, S., & Martini, A. (2006). Balancing mixed-model assembly lines with parallel workstations through a genetic algorithm approach. International Journal of Industrial Engineering, 13(4), 402.Ugurdag, H. F., Rachamadugu, R., & Papachristou, C. A. (1997). Designing paced assembly lines with fixed number of stations. European Journal of Operational Research, 102(3), 488-501. https://doi.org/10.1016/S0377-2217(96)00248-2Wei, N. C., & Chao, I. M. (2011). A solution procedure for type E simple assembly line balancing problem. Computers & Industrial Engineering, 61(3), 824-830. https://doi.org/10.1016/j.cie.2011.05.01

Balancing and Sequencing of Mixed Model Assembly Lines

Assembly lines are cost efficient production systems that mass produce identical products. Due to customer demand, manufacturers use mixed model assembly lines to produce customized products that are not identical. To stay efficient, management decisions for the line such as number of workers and assembly task assignment to stations need to be optimized to increase throughput and decrease cost. In each station, the work to be done depends on the exact product configuration, and is not consistent across all products. In this dissertation, a mixed model line balancing integer program (IP) that considers parallel workers, zoning, task assignment, and ergonomic constraints with the objective of minimizing the number of workers is proposed. Upon observing the limitation of the IP, a Constraint Programming (CP) model that is based on CPLEX CP Optimizer is developed to solve larger assembly line balancing problems. Data from an automotive OEM are used to assess the performance of both the MIP and CP models. Using the OEM data, we show that the CP model outperforms the IP model for bigger problems. A sensitivity analysis is done to assess the cost of enforcing some of the constraint on the computation complexity and the amount of violations to these constraints once they are disabled. Results show that some of the constraints are helpful in reducing the computation time. Specifically, the assignment constraints in which decision variables are fixed or bounded result in a smaller search space. Finally, since the line balance for mixed model is based on task duration averages, we propose a mixed model sequencing model that minimize the number of overload situation that might occur due to variability in tasks times by providing an optimal production sequence. We consider the skip-policy to manage overload situations and allow interactions between stations via workers swimming. An IP model formulation is proposed and a GRASP solution heuristic is developed to solve the problem. Data from the literature are used to assess the performance of the developed heuristic and to show the benefit of swimming in reducing work overload situations

Reducing physical ergonomic risks at assembly lines by line balancing and job rotation: A survey

Factors such as repetitiveness of work, required application of forces, handling of heavy loads, and awkward, static postures expose assembly line workers to risks of musculoskeletal disorders. As a rule, companies perform a post hoc analysis of ergonomic risks and examine ways to modify workplaces with high ergonomic risks. However, it is possible to lower ergonomic risks by taking ergonomics aspects into account right from the planning stage. In this survey, we provide an overview of the existing optimization approaches to assembly line balancing and job rotation scheduling that consider physical ergonomic risks. We summarize major findings to provide helpful insights for practitioners and identify research directions

System approach to the mass production improvement

© 2018, Springer International Publishing AG. The ways of increasing the efficiency of production processes in automotive industry are presented in the article. These ways can be realized by modern optimization methods and tools. Analysis of activity of enterprises implementing strategies of production development, shows that only comprehensive solutions can lead to real improvements. The results of simulation experiments revealed the best combination of input factors values that helped to improve each of factors, compared to existing solutions

Planification socio-responsable du travail dans les chaînes de montage d'aéronefs : comment satisfaire à la fois objectifs ergonomiques et économiques

Dans cette thèse, le problème de planification des tâches dans les chaînes de montage des aéronefs est étudié. Ces lignes de production sont principalement manuelles et tactées. L'échec de la livraison dans les délais pouvant entraîner des pénalités importantes pour le fabricant, il est essentiel de respecter le calendrier de chaque poste de travail en tenant compte à la fois de critères économiques et ergonomiques. Ce problème de planification peut être considéré comme un problème généralisé de planification de projets avec contraintes de ressources (RCPSP). Dans un premier temps, nous passons en revue les méthodes ergonomiques existantes qui peuvent être utilisées pour évaluer la charge de travail physique dans les lignes de production et examinons leur applicabilité au contexte des chaînes de montage d'aéronefs avec des temps de cycle longs. Sur la base de cette évaluation, nous développons des modèles mathématiques à introduire dans les problèmes considérés du RCPSP afin de prendre en compte l'impact ergonomique sur les opérateurs. Tenant compte de ces contraintes ergonomiques, le problème industriel initial est modélisé comme un RCPSP avec des contraintes et des objectifs spéciaux intégrant à la fois des aspects économiques et ergonomiques. Plusieurs formulations avec des opérateurs polyvalents, des ressources avec des capacités dépendantes du temps, des contraintes sur les facteurs ergonomiques et des tâches multimodales ordonnées par des relations de précédence complexes sont considérées. Des modèles de programmation par contraintes et de programmation linéaire en nombres entiers ont été développés pour ces formulations. Afin d'améliorer les procédures de solution, de nouvelles techniques de propagation de contraintes sont proposées et mises en œuvre. Un nouvel algorithme pour le calcul de la borne inférieure est également développé. L'efficacité des modèles et méthodes présentés est validée par des expériences numériques.In this thesis, the scheduling problem of tasks in aircraft assembly lines is studied. These production lines are mainly manual and paced. Since the failure of delivery on time may result in significant penalties for the manufacturer, it is crucial to meet the schedule at each workstation taking into account both economic and ergonomic criteria. This scheduling problem can be considered as a generalized Resource-Constraints Project Scheduling Problem (RCPSP). Firstly, we review the existing ergonomic methods that can be used to evaluate the physical workload in production lines and examine their applicability to the context of aircraft assembly lines with long takt times. On the basis of this evaluation, we develop mathematical models to be introduced in considered RCPSP problems in order to take into account the ergonomic impact on the operators. Taking into consideration these ergonomic constraints, the original industrial problem is modeled as a RCPSP with special constraints and objectives integrating both economic and ergonomic aspects. Several formulations with multi-skilled operators, resources with time-dependent capacities, constraints on ergonomic factors and multi-mode tasks ordered by precedence relations with time lags are considered. Constraint Programming and Integer Linear Programming models are developed for these formulations. In order to enhance the solution procedures, novel constraint propagation techniques are proposed and implemented. A new algorithm for lower bound calculation is developed as well. The efficiency of presented models and methods are validated through numerical experiments

임시 작업자를 활용한 혼합모델 조립라인의 통합적 균형화 연구

학위논문 (석사)-- 서울대학교 대학원 : 산업공학과, 2015. 2. 문일경.이 논문은 단일 제품을 조립하는 일반적인 조립라인 균형화 문제를 복수 제품들을 동시에 조립할 수 있는 혼합 모델 조립라인으로 확장하였으며, 임시 작업자를 고용하여 조립라인을 효율화할 수 있도록 하였다. 이를 고려한 세 가지 버전의 수학적 모형들을 개발하였다. 각 모형의 목표는 모든 직원의 임금과 작업장 비용을 합친 총 비용을 최소화하는 것, 작업장 수가 주어진 상황에서 사이클 시간을 최소화하는 것, 그리고 정해진 작업장 안에서 업무 과부하를 최소화하는 것이다. 제안된 모형들은 숙련된 작업자와 임시 작업자를 동시에 할당하는 사안과 작업들 사이의 선행관계 등 실제 현장에서 적용되는 실용적 특성들을 고려하고 있다. 뿐만 아니라, 총 비용을 최소화할 수 있는 복합유전알고리즘도 개발되었다. 해의 타당성을 보장하고 복합유전알고리즘의 우수성을 높이기 위해 특별한 유전연산자들과 발견적 기법이 사용되었다. 수치실험들을 통해서 복합유전알고리즘의 우수성을 입증하기 위하여 수학적 모형과 비교하였다.This study extends a single-model assembly line balancing problem to an integrated mixed-model assembly line balancing problem by incorporating temporary unskilled workers, who enhance productivity. Three mathematical models are developed to minimize the sum of total workstation costs, salaries of all workers, and cycle times and potential work overload of a predetermined number of workstations. The proposed models are based on particular features of the real-world problem, such as simultaneous assignments of skilled and temporary unskilled workers as well as precedent restrictions among the tasks. Furthermore, a hybrid genetic algorithm that minimizes total operation costs is developed. Special genetic operators and heuristic algorithms are used to ensure feasibility of solutions and make the hybrid genetic algorithm efficient. Computational experiments demonstrate the superiority of the hybrid genetic algorithm over the mathematical models.Chapter 1. Introduction 1 1.1 The assembly line 1 1.1.1 Characteristics of assembly line problem 1 1.1.2 Assembly line balancing problem 2 1.2 The mixed-model assembly line 3 1.2.1 Characteristics of mixed model assembly line problem 3 1.2.2 Mixed model assembly line balancing problem 4 1.3 Literature review 5 1.4 Contributions 9 Chapter 2. Mathematical Models 11 2.1 General features of mathematical models 11 2.2 Problem description 11 2.3 Model Ⅰ 14 2.4 Model Ⅱ 18 2.5 Model Ⅲ 20 Chapter 3. A Hybrid Genetic Algorithm 23 3.1 Chromosome representation 24 3.2 Objective and fitness function 26 3.3 Genetic operator 27 3.3.1 Selection 27 3.3.2 Crossover 28 3.3.3 Mutation 29 3.4 Terminating conditions and parameters 30 Chapter 4. Computational Experiments 31 4.1 Experiments for Model Ⅰ 39 4.2 Experiments for Model Ⅱ 42 4.3 Experiments for Model Ⅲ 46 4.4 Validation of a hybrid genetic algorithm 48 Chapter 5. Conclusions 50 Bibliography 51 Abstract 54Maste

Decision support tool for dynamic workforce scheduling in manufacturing environments \

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (pages 113-116).Scheduling for production in manufacturing environments requires an immense amount of planning. A large number of factors such as part availability, production cost, space constraints and labor supply must be taken into account. Considering these factors, tasks are scheduled into shifts and allocated the required human resources. However, when actual production begins, the original schedule must be updated regularly due to the dynamic nature of the environment. An enormous challenge in these rapidly changing environments is the reallocation of workers to tasks in real-time due to events such as worker absences, emergent tasks and unanticipated delays. The focus of this thesis is the development of a decision support tool that can assist shift supervisors to rapidly generate new worker-task assignments during a shift to ensure that production stays on track. This research discusses the systems engineering development process of the aforementioned decision support tool including the initial planning and analysis, the interface design, and the resource allocation algorithm. The development process was iterative, with evaluations and feedback at every step facilitating the refinement of the tool. Emphasis was laid on creating a collaborative framework between the human operator and the automated planning algorithm. While automated planning algorithms are a critical component of resource allocation systems since they can solve complex multivariate scheduling problems much faster than humans, they are inherently brittle and unable to respond to uncertainties in dynamic environments. Thus, in this system, the human operator is given high-level planning tasks and the ability to set goals, while the automation handles the creation of the detailed planning and scheduling assignments. Another factor that was stressed was the inclusion of ergonomic risk. Worker-task assignments that do not take into account ergonomic risk exposure can lead to repetitive stress injuries over time, causing manufacturing plants to incur substantial medical expenses. Any system that allocates (or re-allocates) workers to tasks must take into account the ergonomic risk that workers are subjected to due to the tasks they perform in the given shift. The system was evaluated through extensive interactions with individuals from an aircraft production line, including senior level management and representative users from the production floor. The evaluations yielded positive results. Both the management and the representative users were able to identify the applicability of the tool immediately, and all individuals agreed that the system could be very useful in real production environments. The shift supervisors from the shop floor affirmed that the tool captured all major pieces of information they consider while making re-planning decisions. To better assess the potential of the tool and to refine it further, future research should initiate pilot studies to compare the proposed tool with current methods used for decision-making, which are paper schedules and best judgment of human operators.by Radhika Malik.M. Eng

A Study of the Effects of Manufacturing Complexity on Product Quality in Mixed-Model Automotive Assembly

The objective of this research is to test the hypothesis that manufacturing complexity can reliably predict product quality in mixed-model automotive assembly. Originally, assembly lines were developed for cost efficient mass-production of standardized products. Today, in order to respond to diversified customer needs, companies have to allow for an individualization of their products, leading to the development of the Flexible Manufacturing Systems (FMS). Assembly line balancing problems (ALBP) consist of assigning the total workload for manufacturing a product to stations of an assembly line as typically applied in the automotive industry. Precedence relationships among tasks are required to conduct partly or fully automated Assembly Line Balancing. Efforts associated with manual precedence graph generation at a major automotive manufacturer have highlighted a potential relationship between manufacturing complexity (driven by product design, assembly process, and human factors) and product quality, a potential link that is usually ignored during Assembly Line Balancing and one that has received very little research focus so far. The methodology used in this research will potentially help develop a new set of constraints for an optimization model that can be used to minimize manufacturing complexity and maximize product quality, while satisfying the precedence constraints. This research aims to validate the hypothesis that the contribution of design variables, process variables, and human-factors can be represented by a complexity metric that can be used to predict their contribution on product quality. The research will also identify how classes of defect prevention methods can be incorporated in the predictive model to prevent defects in applications that exhibit high level of complexity. The manufacturing complexity model is applied to mechanical fastening processes which are accountable for the top 28% of defects found in automotive assembly, according to statistical analysis of historical data collected over the course of one year of vehicle production at a major automotive assembly plant. The predictive model is validated using mechanical fastening processes at an independent automotive assembly plant. This complexity-based predictive model will be the first of its kind that will take into account design, process, and human factors to define complexity and validate it using a real-world automotive manufacturing process. The model will have the potential to be utilized by design and process engineers to evaluate the effect of manufacturing complexity on product quality before implementing the process in a real-world assembly environment

Modelling human performance within manufacturing systems design:from a theoretical towards a practical framework

Computer-based simulation is frequently used to evaluate the capabilities of proposed manufacturing system designs. Unfortunately, the real systems are often found to perform quite differently from simulation predictions and one possible reason for this is an over-simplistic representation of workers' behaviour within current simulation techniques. The accuracy of design predictions could be improved through a modelling tool that integrates with computer-based simulation and incorporates the factors and relationships that determine workers' performance. This paper explores the viability of developing a similar tool based on our previously published theoretical modelling framework. It focuses on evolving this purely theoretical framework towards a practical modelling tool that can actually be used to expand the capabilities of current simulation techniques. Based on an industrial study, the paper investigates how the theoretical framework works in practice, analyses strengths and weaknesses in its formulation, and proposes developments that can contribute towards enabling human performance modelling in a practical way