Improving manufacturing lead time using holistic approach to planning and execution with integrated data structures: numerical simulation and comparison

Manufacturing planning and control (MPC) plays a significant role in effective planning of requirements and execution of those plans. It also influences various performance measures, in particular on-time delivery, which is dependent on many factors including manufacturing lead time. This paper aims to address key issues of infinite loading of resources, lack of forward planning, and limited simultaneous planning capabilities of MRP through a holistic approach to planning of various components and execution of those plans, based on integrated data structures. It is shown that integrated data structures, combining hierarchical single-level BOMs and sequential operations routings using a holistic approach to planning and execution enable reducing lead time by eliminating slack times associated with traditional methods. Furthermore, manufacturing lead time, based on integrated data structures is a true representation of operation times and is shorter compared with traditional lead time. Sensitivity analysis on lead-time with bills-of-materials (BOM) levels and floats shows that the holistic approach to planning and execution with integrated data structures is an effective way of improving lead-time, in particular when product structures involve many levels of BOMs and floats (slack times). The proposed holistic approach provides forward planning, simultaneous planning of components, and finite loading of resources. It is expected that the concept of integrated data structures be extended to model transaction data with process functions (e.g. production order cycle), which would improve overall cycle times by eliminating manual functions associated with current methods.