CSP Dinámico: Un algoritmo dinámico para la resecuenciación en un almacén de líneas en paralelo

[EN] This paper shows the model used for resequencing where a selectivity bank consisting of parallel line segments is applied to reshuffle a given initial sequence and rule violations are to be minimized.[ES] En el presente trabajo se muestra el modelo utilizado para la resecuenciación en una línea de ensamblaje con mezcla de modelos donde un almacén con configuración en líneas en paralelo se utiliza para resecuenciar y minimizar la violación de restricciones de la línea de montaje.El presente trabajo se ha desarrollado gracias a la ayuda DPI2010-18243 del Ministerio de Ciencia e Innovación del Gobierno de España dentro del programa de Proyectos de Investigación Fundamental no orientada, con el título "Coordinación de operaciones en redes de suministro/demanda ajustadas, resilientes a la incertidumbre: modelos y algoritmos para la gestion de la incertidumbre y la complejidad". Este trabajo también ha sido financiado parcialmente a partir del proyecto DPI2011-27633 y título “Programacion de produccion en cadenas de suministro sincronizadas multietapa con ensamblajes/desensamblajes con renovacion constante de productos en un contexto de innovación”Valero-Herrero, M.; Molina Morte, P. (2013). CSP Dinámico: Un algoritmo dinámico para la resecuenciación en un almacén de líneas en paralelo. Working Papers on Operations Management. 4(1):23-33. https://doi.org/10.4995/wpom.v4i1.1234SWORD233341Inman, R. R., & Schmeling, D. M. (2003). Algorithm for agile assembling-to-order in the automotive industry. International Journal of Production Research, 41(16), 3831-3848. doi:10.1080/00207540310001595792Jayaraman, A., Narayanaswamy, R., & Gunal, A. K. (1997). A Sortation System Model, in Simulation Conference, 1997., Proceedings of the 1997 Winter, pp. 866-871.Kittithreerapronchai, O. & Anderson, C. (2003). Do ants paint trucks better than chickens? Markets versus response thresholds for distributed dynamic scheduling, in Evolutionary Computation, 2003. CEC '03. The 2003 Congress on, pp. 1431-1439.Valero-Herrero, M., Garcia-Sabater, J. P., & Maheut, J. (2011b). An approach to the real circumstances of the car sequencing problem, in 41st International Conference on Computers and Industrial Engineering

Productivity optimization of manufacturing system using computer simulation, design of experiment and response surface methodology

Productivity plays a significant role for most companies in order to measure the efficiency. In reality there is an essential need to evaluate the different factors which increasing productivity and achieving the high level of quality, a high production rate and machine utilization. Therefore, in the manufacturing industry, managers and engineers are seeking to find methods in order to eliminate the common problems in manufacturing systems such as bottlenecks and waiting times. This is because that all of these kinds of problems impose extra cost to the companies. In addition, manufacturing companies are striving to sustain their competitiveness by improving productivity, efficiency and quality of manufacturing industry for instance high throughput and high resource utilization. So it can be acquired by finding ways to deal with various industrial problems which have affected the productivity of manufacturing systems such as high lead time and work-in-progress (WIP) and etc. This thesis concentrates on the application of design of experiment (DOE) and computer simulation to recognize and to weight the significance of different factors in the production line as well as to achieve the optimum productivity. Arena 13.9 software was selected as the simulation software. A case study of color industry was chosen to implement and evaluate the result of applying DOE and response surface methodology (RSM) by using Minitab 16 and Expert-Design 6.5. Data required for developing the simulation model were gathered from the factory documents and stop-watch method. The results reveal that applying computer simulation and design of experiment in the manufacturing systems is very useful and helpful where the weakness of the system will be found after doing the experimentation. Based on the main objectives of this thesis the effect of the factors which have the most significant influence on the productivity was assessed and determined. Finally the best factor setting which result in the maximum productivity was determined

Small-World Optimization Algorithm and Its Application in a Sequencing Problem of Painted Body Storage in a Car Company

In the car company, the painted body storage (PBS) is set up between the paint shop and the assembly shop. It stores the vehicles in production and reorders the vehicles sequence. To improve production efficiency of assembly shop, a mathematical model is developed aiming at minimizing the consumption rate of options and the total overtime and idle time. As the PBS sequencing process contains upstream sequence inbound and downstream sequence outbound, this paper proposes an algorithm with two phases. In the first phase, the discrete small-world optimization algorithm (DSWOA) is applied to schedule the inbound sequence by employing the short-range nodes and the long-range nodes in order to realize the global searching. In the second phase, the heuristic algorithm is applied to schedule the outbound sequencing. The proposed model and algorithm are applied in an automobile enterprise. The results indicate that the two-phase algorithm is suitable for the PBS sequencing problem and the DSWOA has a better searching performance than GA in this problem. The sensitivity of model parameters is analyzed as well

Otomotiv montaj hatlarında montaj öncesi ara stok içeriğinin belirlenmesi

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Karma modelli montaj hatlarında hattın düzgün ilerlemesi, üretim kısıtları ve müşteri talepleri doğrultusunda belirlenmiş olan çizelgelenmiş sıraya uyuma bağlıdır. Fakat çizelgelenmiş sıra kasıtlı ve kasıtsız araç sıra değişiklikleri nedeniyle bozulabilmektedir. Bozulan sırayı onarmak için boyahane ile montaj departmanları arasında araç yeniden sıralanma ara stoğu bulunmaktadır. Bu ara stok bozulan sırayı üç farklı şekilde onarmaktadır: Bunlar (i) araç sıralarının değiştirilmesi, araçların yeniden sıralanması, (ii) hatalı araçların ara stokta tutulan araçlarla değiştirilmesi, (iii) son olarak da ara stok kapasitesi ve araç hatalarına bağlı olarak yeniden sıralamayla onarmanın mümkün olmadığı durumda ara stoktan montaj hattına araç beslenmesidir. Tezde, boyahanede rastgele oluşan hataları göz önünde bulunduran iki-aşamalı stokastik programlama modeli geliştirilmiştir. Modelin ilk aşamasında, bozulan sıranın onarılması için yeniden sıralama ara stoğunda tutulması gereken optimal model-renk kombinasyonlarına ait miktarlar belirlenmektedir. İkinci aşamada ise boyahanede oluşan hatalar gözlendikten sonra, araçların montaj giriş sıralarına karar verilmektedir. Problemin çözümü ara stok depolama sistemine bağlı olduğundan, otomatik depolama ve çekme sistemleri (AS/RS) ve yeniden sıralama hatları (mix-bank) için iki ayrı model kurulmuştur. Geliştirilen iki-aşamalı stokastik modelin çözümü örneklem ortalaması yaklaşımı (SAA) ile yapılmış, ara stokta tutulması gereken optimal model-renk kombinasyonlarının miktarları belirlenmiştir. Ayrıca hata oranı, ara stok kapasitesi, araçların boya giriş sıralarının çizelgelenmiş sıraya uyumu gibi problem parametrelerinin çözüme etkisini incelemek için bir sayısal çalışma yapılmıştır. Boya hatalarına bağlı araç sıra değişiklikleri anlık karar vermeye dayandığı için, araç üreticilerinin kolaylıkla uygulayabileceği kural tabanlı, sezgisel alternatif bir model kurulmuştur. Geliştirilmiş olan kural tabanlı model matematiksel modele yakın sonuçlar vermiştir. Son olarak, AS/RS ve yeniden sıralama hatlarında karşılaşılan büyük ölçekli problemleri de çözebilmek için, sunulan model genetik algoritma kullanılarak geliştirilmiştir.In mixed model assembly lines, smooth operation of the line depends on adherence to the scheduled sequence which is determined according to production constraints and customer demand. However, the scheduled sequence is scrambled due to intentional and unintentional sequence alterations. A resequencing buffer between paint and final assembly is located to restore the altered sequence. Restoring the altered sequence requires three distinct operations of this buffer: (i) Changing the positions of vehicles (i.e., resequencing), (ii) replacing spare vehicles with paint defective vehicles, (iii) lastly inserting spare vehicles to final assembly from the buffer when restoring the altered sequence is not possible by resequencing due to paint defects and limited buffer capacity. In this thesis, a two-stage stochastic programming model which considers the stochastic nature of paint defect occurrences is developed. In the first stage of the model, optimal number of model-color types placed into resequencing buffer to restore the scheduled sequence is determined. In the second stage after defect occurrences, the assembly entrance sequences of the vehicles are decided. Since the solution of the problem depends on the resequencing buffer type, two different models for automated storage and retrieval system (AS/RS) and mix-bank are built. The developed two-stage stochastic program is solved by sample average approximation (SAA) algorithm to and the optimal number of model-color types to be placed in the buffer is found. Also a numerical study is performed to investigate the problem parameters to the solution such as paint defect rate, capacity of buffer, adherence ratio of vehicles entering paint shop to scheduled sequence. Since vehicle resequencing due to the paint defects requires instant decision making, another heuristic rule based model to resequence vehicles easily by car manufacturers is developed. The proposed heuristic model performs as good as mathematical model. Lastly, to solve the large scale problems for both AS/RS and mix-bank resequencing buffers the purposed model is enhanced with genetic algorithm