Capacity Planning and Resource Allocation in Assembly Systems Consisting of Dedicated and Reconfigurable Lines

AbstractCompanies with diverse product portfolio often face capacity planning problems due to the diversity of the products and the fluctuation of the order stream. High volume products can be produced cost-efficiently in dedicated assembly lines, but the assembly of low-volume products in such lines involves high idle times and operation costs. Reconfigurable assembly lines offer reasonable solution for the problem; however, it is still complicated to identify the set of products which are worth to assemble in such a line instead of dedicated ones. In the paper a novel method is introduced that supports the long-term decision to relocate the assembly of a product with decreasing demand from a dedicated to a reconfigurable line, based on the calculated investment and operational costs. In order to handle the complex aspects of the planning problem a new approach is proposed that combines discrete-event simulation and machine learning techniques. The feasibility of the approach is demonstrated through the results of an industrial case study

Towards coordination in robust supply networks

Supply chains nowadays frequently face risks caused by increased environmental volatility and performance inefficiency In this paper an integrated supply chain planning approach is suggested that combines the three aspects of optimisation, risk mitigation and decentralisation. The goal of this paper is to outline the research directions for industrially relevant and applicable methods for integrating robust and coordinated supply chain planning. © 201

A termelésirányítás intelligens technikái = Intelligent techniques of production control

A mesterséges intelligencia technikák (sokszor más diszciplínák eredményeivel integrálva) nyújtják talán a legígéretesebb eszközöket (pl. mesterséges neurális hálózatok, fuzzy megközelítések, szakértő rendszerek) az intelligens gyártórendszerek által új kihívások megválaszolására. A szub-szimbolikus technikák (pl. a mesterséges neurális hálók) leginkább az alacsony szintű (pl. folyamat felügyelet), míg a szimbolikus technikák (pl. szakértő rendszerek) a magas szintű (pl. kapacitástervezés) gyártási feladatok megoldásában kerülnek elsősorban alkalmazásra. Ha megvizsgáljuk a magas szintű gyártási problémákat, akkor az alacsony szintűekhez - információfeldolgozási szempontból -kísértetiesen hasonló fogalmakkal, feladatokkal találkozhatunk. Természetesen ezek a feladatok más adatokon alapulnak, különböző paraméterek meghatározását igénylik, egészen eltérő konkrét célokkal és korlátozássokkal rendelkeznek, mégis, felvetődik az alacsony szinten már bevált technikák alkalmazása a termelésirányítás magasabb szintjein is. E feltevés igazolása, és a vonatkozó megoldások kidolgozása volt a kutatás legfőbb célkitűzése. A korábban kidolgozott, publikált vagy alkalmazott technikák nem alkalmazhatóak közvetlenül a magas szintű feladatok megoldására, azokat adaptálni, változtatni volt szükséges. Célunk ezen algoritmusok megvalósítása, tesztelése, alkalmazási feltételeinek meghatározása volt - a magas szintű gyártási feladatok megoldásában. | Artificial intelligence techniques (usually integrating the results of other research fields, too) could serve as one of the most promising tools (e.g. artificial neural networks, fuzzy sets, expert systems) for answering the new assignments of intelligent manufacturing systems. Sub-symbolic techniques (e.g. artificial neural networks) are mainly used on low level, (e.g. process monitoring), while symbolic techniques (e.g. capacity planning) are mainly used on the upper level of manufacturing. Through analysing the decision situations, arising on high-level manufacturing, the existence of quite similar problems can be recognised. Naturally, these tasks require determination of different parameters, they have different targets and constraints, but, the applicability of techniques used with success on low-level manufacturing, on high-level production, too, is still a question. To prove this and to develop the related solutions was the main goal of the research. The already published and used techniques were not directly applicable for solving high-level manufacturing assignments, consequently, they had to be adopted and changed. The analysis and solutions of high-level manufacturing decisions served with new tasks, and required to come up with new ideas, methods, solutions and algorithms. Our goal was to realise and test these algorithms, to identify their application conditions for solving assignments on high-level manufacturing

Simulation-based Production Planning and Execution Control for Reconfigurable Assembly Cells

In order to meet the continuously changing market conditions and achieve economy of scale, a current trend in the automotive industry is the application of modular reconfigurable assembly systems. Although they offer efficient solution to meet the customers needs, the management of these systems is often a challenging issue, as the continuous advance in the assembly technology introduces new requirements in production planning and control activities. In the paper, a novel approach is introduced that enables the faster introduction of modular assembly cells in the daily production by offering a flexible platform for evaluating the system performance considering dynamic logistics and production environment. The method is aimed at evaluating different modular cell configurations with discrete-event simulation, applying automated model building and centralized simulation model control. Besides, the simulation is linked with the production and capacity planning model of the system in order to implement a cyclic workflow to plan the production and evaluate the system performance in a proactive way, before releasing the plan to the production. The method and the implemented workflow are evaluated within a real case study from the automotive industry

Simulation support in construction uncertainty management: A production modelling approach

The execution of construction projects such as a highway construction or the elevation of a new bridge is a complex, highly equipment-intensive process and are subject to many different uncertainties. This is very similar to the manufacturing execution level in production systems where predefined productions plans and schedules cannot be completely implemented due to unexpected internal and external changes and disturbances. Following this analogy, the paper proposes the application of a discrete-event simulation based method which was already applied in the decision-support for manufacturing control to develop the decision-support in the execution of a construction project where the effects of the deviation from the short-term schedule can be easily and quickly analyzed