Introducing the Central Backup Cellular Manufacturing System (CBCMS)

In this paper, we present a new layout arrangement that we call the central backup cellular manufacturing systems (CBCMS). The CBCMS organization is inspired by the concept of the remainder cell in Group technology (GT) systems where the idea is to allocate products that are not easily partitioned in the parts-machine incidence matrix to the remainder cell through a cell that contains all process capabilities. The fractal cell layout can be thought of as replications of the remainder cell in the GT concept. The GT layout represents an efficient approach under certain static conditions, while the fractal layout represents a flexible approach that better deals with uncertainties. The objective of this paper is to explore how a designer can manage variability arising from internal and external disturbances in manufacturing systems while designing a layout and in doing so, to show that the CBCMS provides a framework to unify GT and fractal layouts

Estimating Travel Distances and Optimizing Product Placement for Dedicated Warehouses with Manual Picking

This paper looks at the problem of estimating travel distances for rectangular warehouse sections with manual picking. This study was motivated by a real-life case in the food and beverage industry where case picking occurred in a rectangular section of the warehouse In particular, we are interested in estimating the distance travelled by an order picker whose picking route begins and ends at a single depot. One of the assumptions in many distance approximation papers is that any location is equally likely to be picked. However, this assumption is unrealistic in the case of dedicated warehouse layout, where products are located strategically in order to minimize total distance. The frequency of accessing a pick location can be estimated from the order history table of a WMS. This in turn can be translated into the probability of accessing certain locations. Under the simplifying assumption that there is no backtracking in the aisles, we build a probability tree to estimate the distance traveled by the order picker. From a placement point of view, we present three product assignment (or order slotting) heuristics in this paper, namely the North-North, North-South, and Nearest Neighbor heuristics. Our study shows that there is very little variation between the heuristics in terms of travel distance

Manufacturing strategy using new and reconditioned rotable spare parts

Part of: Seliger, Günther (Ed.): Innovative solutions : proceedings / 11th Global Conference on Sustainable Manufacturing, Berlin, Germany, 23rd - 25th September, 2013. - Berlin: Universitätsverlag der TU Berlin, 2013. - ISBN 978-3-7983-2609-5 (online). - http://nbn-resolving.de/urn:nbn:de:kobv:83-opus4-40276. - pp. 224–229.The process of remanufacturing is attractive economically and environmentally for both manufacturers and consumers. It is important to properly use reconditioned parts in a production plan based on their availability and production costs. A mathematical model is derived to find the cost-optimal production strategy that incorporates reconditioned components in the manufacturing effort. New and reconditioned parts are used to carry out replacements upon failure under an unlimited free replacement warranty policy. Key production decisions, such as when remanufacturing should commence, how long the warranty period should be, and how many returned parts should be reconditioned are answered. The availability of reconditioned parts and their discounted costs are incorporated in the model. Interactions between these decisions and their impacts on the manufacturing system and the consumer are investigated. A case study on aircraft rotable spare parts will be presented

Integrated production quality and condition-based maintenance optimisation for a stochastically deteriorating manufacturing system

This paper investigates the problem of optimally integrating production quality and condition-based maintenance in a stochastically deteriorating single- product, single-machine production system. Inspections are periodically performed on the system to assess its actual degradation status. The system is considered to be in ‘fail mode’ whenever its degradation level exceeds a predetermined threshold. The proportion of non-conforming items, those that are produced during the time interval where the degradation is beyond the specification threshold, are replaced either via overtime production or spot market purchases. To optimise preventive maintenance costs and at the same time reduce production of non-conforming items, the degradation of the system must be optimally monitored so that preventive maintenance is carried out at appropriate time intervals. In this paper, an integrated optimisation model is developed to determine the optimal inspection cycle and the degradation threshold level, beyond which preventive maintenance should be carried out, while minimising the sum of inspection and maintenance costs, in addition to the production of non-conforming items and inventory costs. An expression for the total expected cost rate over an infinite time horizon is developed and solution method for the resulting model is discussed. Numerical experiments are provided to illustrate the proposed approach

Optimizing the integrated economic production quantity for a stochastically deteriorating production system under condition-based maintenance

This paper proposes a new integrated economic production quantity (EPQ) and condition-based maintenance (CBM) model for a stochastically deteriorating production system. Inspections are performed periodically to measure the real time degradation. The system fails (out-of-control) whenever its degradation is beyond a critical threshold level. In the out-of-control state, a proportion of nonconforming items are produced. To assess the degradation of the system and to increase the production of conforming items, preventive maintenance (PM) actions are carried out. An integrated EPQ and CBM optimization model that minimizes the total expected cost rate over an infinite time horizon is developed. The objective is to determine a joint optimal EPQ and PM strategy minimizing the sum of inspection/maintenance and setup costs, cost of nonconforming items in addition to inventory holding cost. Numerical experiments are provided to illustrate the proposed approach

An approach to model and manage cost-risk trade-off in Networked Manufacturing

Le présent article introduit une évaluation du risque dans la planification des systèmes manufacturiers, impliquant différents acteurs travaillant séquentiellement pour réaliser un produit. Nous considérons ici un environnement dynamique virtuel, où différentes firmes soumissionnent pour des taches précises. L’approche traditionnelle est d’assigner des firmes à des taches pour minimiser les coûts d’utilisation de la chaîne. Cette approche néglige ainsi la notion de fiabilité et de risque. L’objectif de cet article est de proposer une façon d’incorporer la notion de risque au processus de planification de la chaîne. Nous avons identifié le risque comme une combinaison de trois principaux intrants, et nous l’évaluons grâce à une approche dérivée de la logique floue. Nous décrivons comment fonctionne notre programme, et comment le risque évalué est utilisé pour établir quelles firmes choisir afin d’optimiser le compromis coût-risque.This paper introduces elements of risk into supply-chain manufacturing systems that involve various actors acting sequentially to achieve an end-result. We consider a virtual dynamic environment, where different firms bid on sequential tasks. The traditional approach has been to assign tasks to firms, in order to realize production as cost-effective chains of activities. This approach neglects elements of risk, which we show how to incorporate. We have identified risk as a combination of three inputs, using a fuzzy logic approach. We show how a fuzzy controller can measure the risk involved in a supply-chain, which is constructed on an order-contract basis. We use this measure of risk to build a decision support environment that helps isolate alternative supply-chains that are potentially interesting from a cost perspective and compares them from a risk minimization stand point.