A system dynamics archetype to mitigate rework effects in engineer-to-order supply chains

There are established archetypes that demonstrate the dynamic properties of make-to-order/stock and assemble -to-order production planning and inventory control systems and their impact on total on-costs, allowing for performance benchmarks to be established. However, the dynamic properties of engineer-to-order (ETO) pro-duction system, where products are designed and made to a specific customer order, are not well understood. Time and cost-overrun, poor capacity planning and high rates of rework are difficulties faced by ETO managers and, for now, solutions for these problems are still lacking.Therefore, this paper develops an ETO production model which merges a service-orientated design subsystem with a working-unit-orientated production subsystem to establish an order book-controlled ETO system. The developed model realises automatic capacity control to maintain the expected lead time and order book. At the same time, we also conduct transfer function and stability analysis on this holistic ETO model to investigate the system's dynamic properties using Control Theory and System Dynamics.This paper's contributions could be summarised from four perspectives. 1. It provides an automatic capacity -controlled archetype for practice benchmarking and demonstrating the advantage of a whole system level order book controller. 2. The order book proportional controller, at a whole system level rather than just in the local subsystems, can offset the rework's negative impact, while achieving target order book and service times. 3. The dynamic analysis provides transfer functions, demonstrating the dynamic relationship between demand (input) with order book and lead time (outputs). 4. The derived critical condition for system stability provides guidelines for system managers to prevent the system becoming unstable.The limitation of this paper is that we assume the rework could only happen in the production system and could be rectified in the production system. However, in practice, rework could happen and be detected everywhere. Further research could relax this assumption and explore the dynamics of these scenarios.