Abstract

Customized manufacturing, particularly in the window production industry, presents unique challenges in sequencing and scheduling due to the variability in product attributes such as size, color, and delivery deadlines. Traditional batch processing methods often fall short in addressing these complexities, leading to inefficiencies in fabrication and assembly lines. This paper proposes the design of an intelligent sequencing tool tailored for configured manufacturing environments. By integrating attribute-based sequencing algorithms and dynamic scheduling techniques, the tool aims to optimize production flow, reduce downtime, and enhance responsiveness to rush orders. The study delves into the specific challenges of customized window manufacturing, explores existing literature on sequencing and scheduling in mass customization, and presents a methodology for developing the proposed tool. Results from simulated environments demonstrate improved line balancing and throughput, indicating the tool's potential applicability in real-world settings.
In customized window production, complexity arises not only from the variety in product configurations but also from the need to sequence fabrication in alignment with assembly line capacities and delivery priorities. Moreover, the system must respond to disruptions such as late orders, rush requests, and material shortages without creating downstream bottlenecks. Traditional ERP systems or generic planning tools are insufficient for handling such real-time decisions based on dynamic attribute combinations. The proposed tool introduces a modular approach that factors in sequencing rules specific to industries like windows—such as color-based grouping, size constraints, and delivery clustering. It uses rule-based logic and AI-driven scheduling that continuously adapts to manufacturing flow. This paper also evaluates cost-saving potentials and operational benefits of transitioning from manual or semi-automated scheduling to intelligent, automated sequencing. As industries move toward greater customization and lean manufacturing principles, such tools can bridge the gap between flexibility and efficiency.