An analysis of energy-efficient production control strategies in serial systems with two nonidentical machines

Abstract This study investigates energy-aware production control in a make-to-stock manufacturing system with two serially connected, non-identical machines operating in multiple energy modes such as production (on), standby, and off. Motivated by the growing need to reduce industrial energy consumption while maintaining service levels, we model the system as a continuous-time Markov decision process (MDP) and solve it exactly using a linear programming approach. Our analysis explores how demand rate, sales price, production capacity, and energy costs interact with the bottleneck location to influence key performance metrics such as long-run average profit, inventory levels, service levels, and machine utilization. We further compare the optimal energy-efficient policy with the widely used always-on policy, under which machines remain powered on and operate in either Production or Standby mode to mitigate lost sales. Numerical experiments based on a full factorial design reveal that system profitability and efficiency are primarily driven by demand intensity, sales margins, and bottleneck shifts, whereas variations in energy tariffs have relatively minor effects. Importantly, we show that the always-on policy can approximate the optimal solution under high demand or high-margin conditions, but leads to substantial inefficiencies when demand is low. These insights provide practical guidance for implementing energy-saving strategies in industrial production lines without compromising service performance.