An Application of a Decision Support System Enabled by a Hybrid Algorithmic Framework for Production Scheduling in an SME Manufacturer

Abstract

In this research, we present a hybrid algorithmic framework and its integration into the precise production scheduling system of a Greek metal forming factory. The system was created as a decision support tool to assist production planners in arranging weekly production orders to work centers and other manufacturing cells. The functionality offered includes dispatching priority rules, bottleneck identification for capacity planning, production order reallocation to alternate work centers and planning periods, interchangeable scheduling scenarios, and work-in-process availability checks based on bill of materials (BOM) precedence constraints. As a consequence, a solid short-term production plan is created, capable of absorbing shop floor risks such as machine failures and urgent orders. The primary design ideas are simplicity, ease of use, a flexible Gantt-chart-based graphical user interface (GUI), controllable report creation, and a modest development budget. The practical application takes place in a make-to-stock (MTS) environment with a complicated multi-level production process, defined due dates, and parallel machines. A critical component is the integration with legacy applications and the existing enterprise resource planning (ERP) system. The method adopted here avoids both overburdening the existing information system architecture with software pipeline spaghetti, as is common with point-to-point integration, and overshooting implementation costs, as is often the case with service-oriented architectures.

Keywords

• production scheduling
• decision support
• scheduling algorithms
• hybrid metaheuristics
• dynamic job shops
• practical application