This paper deals with a real-life case study of a Chinese medical device manufacturer. This manufacturer receives orders and delivers products ahead of schedule. A small proportion of orders may not be fulfilled on time due to capacity constraints, changes in demand, etc. These products often have a similar manufacturing process and share the same resources. These products often have a similar manufacturing process and share resources. Items are processed in parallel orders. A multi-stage scheduling decision model is formulated to help production planners make three decisions: (i) whether or not to accept orders; (ii) whether or not to switch demand to produce; (iii) whether or not to adjust production plans. The proposed model takes account of real-time situations in the Production Planning and Control (PPC) system to increase profitability, balance workloads, and avoid delays. Delays in updating demand information and unavailable resources are taken into account. Short- and long-term production plans are synchronized in a multi-level scheduling decision model.

Sustainable scheduling problem has attracted great attention in academia due to the importance of sustain-ability from economical-, environmental- and social-oriented dimensions.). Based on previous studies on the choices of sustainable indicators, system sustainability of production plan-ning and control (PPC) is still perceived to be difficult to be achieved by practitioners. Short-term objectives often conflict with medium- and long-term objectives due to changing de-mands, uncertainties of the shortage of machines and materials and labour's attendance. Previous studies on lot-sizing and scheduling only consider increasing responsiveness to changing or uncertain demands, instead of considering decisions of switching demands. A multi-stage decision-making model for sustainable scheduling in a hybrid flexible flow shop (HFFS) is formulated to take account of whether to accept demands and switch demand from one to the other for achieving system sustainability in this study. This model has been validated by a Chinese medical goods company.