Master production schedule time interval strategies in make-to-order supply chains¶

Abstract

While the literature primarily addresses MPS design from the manufacturer's perspective, this research considers MPS policy design in a two-stage rolling schedule environment with a particular focus on the policy governing schedule flexibility in the non-frozen time interval (i.e. liquid versus slushy orders). Using computer simulation, we experimentally evaluate the impact of four MPS design factors (non-frozen interval policy, planning horizon length, frozen interval length and re-planning frequency) and four environmental factors (natural order cycle length, vendor flexibility, demand range and demand lumpiness) on MPS schedule cost and instability. The experimental design considers the oftenconflicting impact of MPS policy on the channel members by capturing performance metrics at the manufacturer, vendor and system level. The research findings indicate that moving from a liquid to a slushy non-interval strategy increases the manufacturer's costs, but may result in an even greater cost reduction for the vendor resulting in lower system costs. The economic benefit of the slushy strategy is directly tied to the vendor's relative flexibility in responding to the manufacturer's orders on a lot-for-lot basis. High vendor flexibility favours the liquid strategy, while low vendor flexibility favours the slushy strategy.

Supplier performance and selection from sustainable supply chain performance perspective

“…Over the period, it has been proven that having suppliers who provide high-quality products with minimum cost positively affects manufacturing and SCP (John et al, 2006;Beamon, 1999;Kannan and Tan, 2005). Several studies showed that the effective use of the master production schedule is very important for better manufacturing performance (Gunasekaran et al, 2001;Bhagwat and Sharma, 2007;Robinson et al, 2008;Cho et al, 2012).…”

“…Several studies showed that the effective use of the master production schedule is very important for better manufacturing performance (Gunasekaran et al. , 2001; Bhagwat and Sharma, 2007; Robinson et al. , 2008; Cho et al.…”

An Agent-Based Approach for Make-To-Order Master Production Scheduling

“…They conducted full-factorial experiments to define the main drivers of MPS policy cost and schedule stability. Powell Robinson, Sahin, and Gao (2008) also develop a two-stage rolling schedule environment with a particular focus on the policy related to the schedule flexibility in the non-frozen time intervals [26]. Sawik (2007) explored the same topic by developing multi-objective, long-term production scheduling in an MTO environment and a lexicographic approach with a hierarchy of integer programming formulations [27].…”