ABSTRACT
The need to increase the service level of the automotive supply chain, especially after the COVID-19 pandemic, leads to an increase in the efficiency and effectiveness of the production systems. The use of scheduling techniques and their implementation in Enterprise Resource Planning (ERP)/ Manufacturing Execution System (MES) systems can be a lever towards this improvement, remarkably in particularly constrained production systems. The presented case study stems from an industrial context and focuses on the heating and cooling phases of curved glass used in the automotive sector. In particular, the glass is subjected to a gradual heating process at temperatures between 500 and 600 °C, after which it softens and adheres by force of gravity to a curved mold located on the bottom of the heated room. The cooling phase takes place very slowly, to allow the material to acquire a greater flexural strength than a normal flat glass. The objective of this study is to present a scheduling algorithm to optimize the production of the curve glasses with different technical characteristics and heating and cooling phases. The implementation of this algorithm in the industrial context permits the increase of the ovens’ saturation and the respect of the delivery date of the production orders. © 2022, AIDI - Italian Association of Industrial Operations Professors. All rights reserved.
ABSTRACT
In last years, we are facing on the diffusion of on-line orders, a process further accelerated by the spread of the COVID-19 virus. A fundamental lever in the use of the e-Commerce is the continuous reduction of the fulfillment time. In order to obtain these improvements, the storage method has been revolutionized. In fact, we are talking about Online order fulfillment warehouses (F-Warehouses) which, unlike traditional warehouses, have a very large number of small bin locations, an explosive storage policy, where an incoming bulk is separated into small lots stocked in any bin throughout the warehouse, and commingled bin storage. The divided warehouse (M-Division) with explosive storage is a novel design, where the warehouse is divided in M-zones managed by specific pickers. In this paper we model the fulfillment process as an N server queuing model with uniform service times and compare the fulfillment time of the traditional warehouse with the M-Division warehouse. In particular, an analytical solution assigns items to the M-Division warehouse in order to minimize the fulfillment time. The results show that the M-Division approach permits a reduction of the fulfillment time compared with the traditional one. © 2021, AIDI - Italian Association of Industrial Operations Professors. All rights reserved.