SIMULATION-BASED DECISION MODEL TO CONTROL DYNAMIC MANUFACTURING REQUIREMENTS: APPLICATION OF GREY FORECASTING - DQFD

Manufacturing systems have to adapt to changing requirements of their internal and external customers. In fact, new requirements may appear unexpectedly and may change multiple times. Change is a straightforward reality of production, and the engineer has to deal with the dynamic work environment. In this perspective, this paper proposes a decision model in order to fit actual and future processes’ needs. The proposed model is based on the dynamic quality function deployment (DQFD), grey forecasting model GM (1,1) and the technique for order preference by similarity to ideal solution (TOPSIS). The cascading QFD-based model is used to show the applicability of the proposed methodology. The simulation results illustrate the effect of the manufacturing needs changes on the strategic, operational and technical improvements

Contribution à la modélisation des approches de coopération en e-maintenance.

International audienceCe travail traite des problèmes liés à la modélisation de la coopération entre différents agents (experts) situés à diffé-rents endroits, pour aider à diagnostiquer et à réparer des défaillances, dans un contexte de e-maintenance. Nous propo-sons des façons d'organiser la coopération entre les experts et de rendre l'information nécessaire à leur diagnostic suffi-samment disponible. Ceci tenant compte de plusieurs facteurs dont la disponibilité des experts, le caractère hétérogène des moyens de communication, et l'évolution dans le temps de l'état des installations à maintenir. Pour cela, nous avons adopté une méthodologie basée sur les modèles de Trenteseau, utilisant également les réseaux de Petri et la simulation. Des résultats de simulation de différentes situations seront présentées et discutées par rapport aux hypothèses et aux indicateurs de performances adoptés

Contribution of simulation to the optimization of maintenance strategies for a randomly failing production system

International audienceThis paper compares two strategies for operating a production system composed of two machines working in parallel and a downstream inventory supplying an assembly line. The two machines, which are prone to random failures, undergo preventive and corrective maintenance operations. These operations with a random duration make the machines unavailable. Moreover, during regular subcontracting operations, one of these machines becomes unavailable to supply the downstream inventory. In the first strategy it is assumed that the periodicity of preventive maintenance operations and the production rate of each machine are independent. The second strategy suggests an interaction between the periods of unavailability and the production rates of the two machines in order to minimize production losses during these periods. A simulation model for each strategy is developed so as to be able to compare them and to simultaneously determine the timing of preventive maintenance on each machine considering the total average cost per time unit as the performance criterion. The second strategy is then considered, and a multi-criteria analysis is adopted to reach the best cost-availability compromise

A decision model for adopting an extended two-dimensional warranty region under different maintenance policies

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Integrated model of preventive maintenance, quality control and buffer sizing for unreliable and imperfect production systems

International audienceIn this paper, we develop a joint quality control and preventive maintenance policy for a randomly failing production system producing conforming and non-conforming units. The considered system consists of one machine designed to fulfil a constant demand. According to the proportion l of non-conforming units observed on each lot and compared to a threshold value lm, one decides to undertake or not maintenance actions on the system. In order to palliate perturbations caused by the stopping of the machine to undergo preventive maintenance or an overhaul, a buffer stock h is built up to ensure the continuous supply of the subsequent production line. A mathematical model is developed and combined with simulation in order to determine simultaneously the optimal rate, l*m and the optimal size h* which minimize the expected total cost per time unit including the average costs related to maintenance, quality and inventory

Simultaneous determination of production lot size and preventive maintenance schedule for unreliable production system

International audiencePurpose - The purpose of this study is to propose and model an integrated production-maintenance strategy for unreliable production systems producing conforming and non-conforming items. Design/methodology/approach - The proposed integrated policy is defined and modeled mathematically. Findings - The paper focuses on finding simultaneously the optimal values of the lot size Q and the age T at which preventive maintenance must be performed. These values minimize the total average cost per time unit over an infinite horizon. Practical implications - The paper attempts to integrate in a single model the three main aspects of any manufacturing system: production, maintenance, and quality. It deals with the lot-sizing problem for a production system which may randomly shift to an out-of-control state and produce non-conforming units. The system is submitted to an age-based preventive maintenance policy. The effect of performing preventive maintenance on quality- and inventory-related costs is shown through a numerical example. Originality/value - The paper proposes an integrated model that links EMQ, quality and an age-based preventive maintenance policy. It is shown that performing preventive maintenance yields reduction in inventory- and quality-related costs

Transportation Needs of Entrepreneurs in Wroclaw Agglomeration – Study Results

This paper deals with the integrated supply chain management problem in the context of a single vendor-single buyer system for which the production unit is assumed to randomly shift from an in-control to an out-of-control state. Two different strategies, integrating production, shipment and maintenance policies, are proposed and compared to satisfy the buyers order at a minimum integrated total cost rate. The first strategy is based on a classical production policy for which the buyer’s order of size nQ is manufactured continuously and shipped by lots of size Q. The second strategy suggests that the same buyer’s order should be produced and shipped separately by equal sized lots Q. For both strategies, a corrective or preventive maintenance action is performed at the end of each production cycle, depending on the state of the production unit, and a new setup is carried out. The total integrated average cost per time unit is considered as the performance criterion allowing choosing the best policy for any given situation