## 3 A Decision Support System for Detailed Scheduling  
### DSS Implementation Overview  
The SME's complicated manufacturing process, along with the limitations of the underlying IT infrastructure, would be a considerable impediment to implementing a commercial advanced planning and scheduling (APS) package to meet the comprehensive production scheduling requirements stated in the preceding section. In light of this, the chosen option was to construct a custom-built DSS that was tailored to the aforementioned manufacturing process and was completely compatible with both the PPC system and the ERP software package. As of 2019, the SME has begun exploring the possibility of reengineering its basic manufacturing process. The decision was made to include the detailed production scheduling layer in the two-tier planning structure. In this regard, it was thought critical to support both the new planning process and the detailed scheduling layer with a low-cost custom-built application that was completely compatible with the other IT infrastructure, particularly the PPC and the ERP system. Reengineering was projected to take 18 months, and during the last three months, a research subproject for application development was begun. To conclude the original application, it was subjected to a testbed of trials and varied use situations. As a consequence, the suggested Gantt-based DSS (G-DSS), was created, including all of the aforementioned features and approaches. G-DSS was developed using visual basic (VB).NET as the programming language and Microsoft Access 2019 as the database management. The latter was necessitated given the existing PPC database structure, which also makes use of Microsoft Access. The primary design concepts were ease of use, scalability, interoperability, simplicity, a flexible graphical user interface, manageable report creation, and a minimal development budget. The installation focused just on the shop floor, rather than the full supply chain, as most commercial APS packages do. This technique was chosen to save development costs and maintain the simplicity of the final DSS, since supply chain optimization is primarily aimed at make-to-order scenarios. Despite the absence of an upstream (suppliers) or downstream (customers) chain, significant attention is placed on pre-subcontractor orders and dispatch outsourcing. The new hierarchical planning framework follows the following procedure: The MPS forecasts long-term end item requirements and feeds the PPC system, which generates the backlog of manufacturing orders. The G-DSS system eliminates backlog orders, assigns them to work centers, and generates comprehensive schedules. Usually, the planner will run the G-DSS at the start of each planning period (which is typically a week), extracting the most recent production order data. Schedules will be prepared for each product group and sent to the foremen prior to the start of production. If dynamic events occur, for example, a rush order is received, a machine fails, or a subcontractor misses a deadline, the planner reschedules to meet them. The whole procedure is repeated weekly. Due to the planner's need for manual control over release/dispatch and quick rescheduling, as well as the frequent occurrence of dynamic events as a result of substantial outsourcing, the construction of a myopic independent optimization suite was judged unnecessary. Additionally, owing to the massive number of production orders, subcontractors, and parallel work centers that classify the scheduling issue in question as NP-hard, the development of an efficient approximation method was regarded as unrealistic in terms of processing time and schedule quality. Rather than that, the study team chose simple but effective priority dispatching rules and a suite of supplementary decision support tools that enable rapid production schedule development, what-if analysis, and rapid rescheduling to meet dynamic occurrences.