Preprint Article Version 1 This version is not peer-reviewed

Supplier Replacement Model in a One-Level Assembly System under Lead-Time Uncertainty

Version 1 : Received: 20 March 2020 / Approved: 23 March 2020 / Online: 23 March 2020 (01:05:03 CET)

A peer-reviewed article of this Preprint also exists.

Afsar, H.-M.; Ben-Ammar, O.; Dolgui, A.; Hnaien, F. Supplier Replacement Model in a One-Level Assembly System under Lead-Time Uncertainty. Appl. Sci. 2020, 10, 3366. Afsar, H.-M.; Ben-Ammar, O.; Dolgui, A.; Hnaien, F. Supplier Replacement Model in a One-Level Assembly System under Lead-Time Uncertainty. Appl. Sci. 2020, 10, 3366.

Journal reference: Appl. Sci. 2020, 10, 3366
DOI: 10.3390/app10103366

Abstract

Supplier selection/replacement strategies and optimized purchasing policies play a key role in efficient supply chain management in today’s dynamic market. Here we study supplier replacement in a one-level assembly system (OLAS) producing one type of finished product. To assemble the product, we need to provide multi-type components, but assembly will be interrupted if any single component is missing, and incoming units will get hoarded until the missing component arrives. The assembly process can be interrupted by various sources of uncertainty, including delays in component deliveries. There is consequently a non-negligible risk that the assembly process may get stopped any moment. This brings inventory-related costs, which should be minimized. Here we consider discrete lead-time distributions to mimic industry-world reality. We present a model that takes into account not only optimal assignment of component order release dates but also replacement of a critical supplier. For a given unit, we model several alternative suppliers with alternative pricing and lead-time uncertainties, and we evaluate the impact on the total assembly system. For a more general case where several suppliers may be replaced, we propose a genetic algorithm.

Subject Areas

assembly systems; replenishment; stochastic lead times; holding cost; backlogging cost; purchase cost; optimization

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.