Dynamic lot sizing and tool management in automated manufacturing systems

Cataloged from PDF version of article.The overall aim of this study is to show that there is a critical interface between the lot sizing and tool management decisions, and these two problems cannot be viewed in isolation. We propose "ve alternative algorithms to solve lot sizing, tool allocation and machining conditions optimization problems simultaneously. The "rst algorithm is an exact algorithm which "nds the global optimum solution, and the others are heuristics equipped with a look-ahead mechanism to guarantee at least local optimality. The computational results indicate that the amount of improvement is statistically signi"cant for a set of randomly generated problems. The magnitude of cost savings is dependent on the system parameters

Modeling Industrial Lot Sizing Problems: A Review

In this paper we give an overview of recent developments in the field of modeling single-level dynamic lot sizing problems. The focus of this paper is on the modeling various industrial extensions and not on the solution approaches. The timeliness of such a review stems from the growing industry need to solve more realistic and comprehensive production planning problems. First, several different basic lot sizing problems are defined. Many extensions of these problems have been proposed and the research basically expands in two opposite directions. The first line of research focuses on modeling the operational aspects in more detail. The discussion is organized around five aspects: the set ups, the characteristics of the production process, the inventory, demand side and rolling horizon. The second direction is towards more tactical and strategic models in which the lot sizing problem is a core substructure, such as integrated production-distribution planning or supplier selection. Recent advances in both directions are discussed. Finally, we give some concluding remarks and point out interesting areas for future research

Dinamičko planiranje i terminiranje uz više kriterija u proizvodnji tokarenih dijelova

Technical innovations in the area of manufacturing logistics are being introduced partially and thus not exploiting their full potential. In order to optimise the efficiency of turning manufacturing processes, the process has been analysed and fundamentally re-engineered. All data from production (operations, quantities, date, time duration of operations, etc.) are now located in ERP system. It provided the necessary condition for the establishment of a robust dynamic planning model. An update was required for the whole lifecycle of products and means of work. The paper presents the information support and an algorithm for a dynamic planning model, based on a genetic algorithm. Continuous data capturing and planning in real time are a breakthrough in the management of the process. Presented are a generalised dynamic planning model and a case example from the production of turned parts, which take account of the singularities of a real environment. Production capacities have to be linked up with the supply chain and customers. The presented dynamic planning model can be adapted to various types of production.U području proizvodne logistike tehničke se inovacije uvode parcijalno te se ne koristi njihov puni potencijal. U cilju poboljšanja efikasnosti proizvodnih procesa tokarenja, postupak se analizirao i u potpunosti preradio. Svi se podaci iz proizvodnje (operacije, količine, datumi, vrijeme trajanja operacija itd.) sada nalaze u ERP sustavu. On je osigurao potrebne uvjete za stvaranje modela dinamičkog planiranja. Tražili su se ažurirani podaci o cijelom radnom vijeku proizvoda i sredstvima za rad. U članku se predstavlja informatička podrška i algoritam za dinamički model planiranja, zasnovan na genetskom algoritmu. Stalno dobivanje podataka i planiranje u realnom vremenu predstavljaju važan napredak u upravljanju tim procesom. Predstavljen je generalizirani model dinamičkog planiranja i primjer iz proizvodnje tokarenih dijelova gdje se uzimaju u obzir specifičnosti stvarnog okruženja. Proizvodni se kapaciteti moraju povezati s nabavnim lancem i kupcima. Ovaj se model dinamičkog planiranja može adaptirati različitim tipovima proizvodnje

Meta-Heuristics for Dynamic Lot Sizing: a review and comparison of solution approaches

Proofs from complexity theory as well as computational experiments indicate that most lot sizing problems are hard to solve. Because these problems are so difficult, various solution techniques have been proposed to solve them. In the past decade, meta-heuristics such as tabu search, genetic algorithms and simulated annealing, have become popular and efficient tools for solving hard combinational optimization problems. We review the various meta-heuristics that have been specifically developed to solve lot sizing problems, discussing their main components such as representation, evaluation neighborhood definition and genetic operators. Further, we briefly review other solution approaches, such as dynamic programming, cutting planes, Dantzig-Wolfe decomposition, Lagrange relaxation and dedicated heuristics. This allows us to compare these techniques. Understanding their respective advantages and disadvantages gives insight into how we can integrate elements from several solution approaches into more powerful hybrid algorithms. Finally, we discuss general guidelines for computational experiments and illustrate these with several examples

Dynamic lot sizing and tool management in automated manufacturing systems

The overall aim of this study is to show that there is a critical interface between the lot sizing and tool management decisions, and these two problems cannot be viewed in isolation. We propose five alternative algorithms to solve lot sizing, tool allocation and machining conditions optimization problems simultaneously. The first algorithm is an exact algorithm which finds the global optimum solution, and the others are heuristics equipped with a look-ahead mechanism to guarantee at least local optimality. The computational results indicate that the amount of improvement is statistically significant for a set of randomly generated problems. The magnitude of cost savings is dependent on the system parameters. In most of the studies on tool management, lot sizes are taken as a predetermined input while deciding on tool allocations and machining parameters. This might create empty feasible solution spaces and otherwise unnecessarily limit the number of alternatives possible for the tool management problem. In this study, we consider the integration of lot sizing and tool management problems ot minimize total production cost for multiple periods under dynamic demand. By integrating these decisions we not only improve the overall solution, but also prevent any infeasibility that might occur for the tool management problem due to decisions made at the lot sizing level. © 2002 Elsevier Science Ltd. All rights reserved

Resolución del problema del tamaño de lote multinivel capacitado aplicando optimización por enjambre de partículas con búsqueda local

Un problema que se presentan en los sistemas de manufactura de las empresas, especialmente pequeñas y medianas empresas, es que la programación de la producción está basada bajo modelos de arrastre de la demanda deterministas, es decir, el proceso de la planificación de los tamaños de lotes de insumos o componentes para la fabricación de productos finales que poseen jerarquías multiniveles y restricciones de capacidad como horas hombres, números de maquinas entre otras, son un problema que se pueden convertir en oportunidades de mejora debido a que se pueden equilibran los costos de ordenamiento de un lote y los costos de inventarios por productos que permita obtener una reducción en los costos totales y así mejorar la productividad de las empresas. Este trabajo presenta una metodología para la solución del problema del tamaño de lote multinivel capacitado, basado en una técnica metaheurísticas llamada optimización por enjambre de partículas o PSO por sus siglas en ingles (Particle Swarm Optimization), la cual se ha demostrado que tiene un buen desempeño dentro de las familia de metaheurísticas, así que se propone el desarrollo de este tema agregando el concepto una búsqueda local que permita generar óptimos locales y permita mejorar las soluciones encontradas por las partículas, denominando a está técnica como la utilización de una hiperheurística.Incluye bibliografía, anexo

Lotsizing and scheduling problems

Diese Magisterarbeit gibt einen Überblick über Losgrößen- und Reihefolgeplanungsprobleme. Losgrößenplanung und Reihefolgeplanung sind integrale Bestandteile der Produktionsplanung. Sie geben an wie viele Produkte und in welcher Reihenfolge diese produziert werden sollen, um die Gesamtkosten zu minimieren. Der Hauptteil der Arbeit beschäftigt sich mit der Darstellung der unterschiedlichen Problemverfahren. Diese werden anhand von Definitionen, mathematischen Formulierungen und Beispielen dargestellt. Zu Beginn der Arbeit wird das Produktionsplanungssystem (PPS) erläutert (in Kapitel 1.1). Dann werden die Definitionen von Losgrößenplanung und Reihefolgeplanung und ihr Zusammenhang erklärt (in Kapitel 2). Darauf folgen eine allgemeine Problembeschreibung und die verschiedenen Kriterien für Losgrößen- und Reihefolgeplanungsprobleme (in Kapitel 3). Im Hauptteil werden die verschiedenen Problemtypen aufgelistet. Es werden einstufige unkapazitierte (in Kapitel 4) und einstufig kapazitierte Probleme (in Kapitel 5), genauso wie mehrstufige Probleme (in Kapitel 6) und Probleme auf mehreren Maschinen (in Kapitel 7) erklärt. Ebenfalls wird die hierarchische Integration von Losgrößen- und Reihefolgeplanungsproblemen beschrieben (in Kapitel 8). Zuletzt werden ein Vergleich der unterschiedlichen Verfahren dargestellt (in Kapitel 9) und die möglichen Lösungsverfahren (in Kapitel 10) behandelt