An industrial scenario-based approach to integrating maintenance and quality planning

This paper presents a novel industrial scenario-based approach to integrating maintenance and quality planning. First, a new preventive maintenance planning model is formed. Herein, to account for reality, different dependencies between the constituent components of a complex multi-component machine are evaluated simultaneously, such as stochastic, structural, and economic. It also serves as a foundation for their complex mathematical formulation. Several potential failure modes in which these components can fail are exhibited. Additionally, the influence of such failures on multiple product quality aspects is well-thought-out in the modelling. Successively, we leverage the inter-dependencies between machine maintenance and product quality to build a realistic integrated plan, defying all existing model assumptions, such as a single critical to quality characteristics for part inspection; perfect machining and maintenance process; deterministic process time for manufacturing/maintenance/inspection, and many more. As a result, operation costs are optimised, including overlooked costs linked to detected and undetected rejects. Besides, a simulation-based optimisation algorithm is offered to overcome the integrated operations planning computing complexity. Making it more responsive in a dynamic industrial scenario perceived in digital cum intelligent enterprises. Finally, it is evaluated in a realistic shop floor scenario to expand the model’s robustness and relevance. This revealed significant cost savings over existing fixed interval policies in an industrial scenario where machines are capital intensive, components are interdependent, machine failure modes are numerous, and various quality characteristics are affected by a failure of the machine. To conclude, the superiority of this approach is then generalised to a broad range of industrial environments.