Cost optimization decision-support based on fuzzy logic applications, advancing industry 4.0

Corporate functions of large multinationals are globally executed based on business processes. Numerous business process variables have impacts on the execution of business functions. A representative subset of business process variables, specifically cost associated, is explored in this research. Cost optimization in the execution of business processes is essential in ensuring corporate sustainability and competitiveness. To develop and implement a cost optimization framework, global best practice cost optimization levers are explored. This research demonstrates the prospects of developing a cost optimization decision-support paradigm based on the fuzzy logic system. Decision-support is an intricate aspect of any business unit. The decision-support framework relative to optimizing cost is explored based on selected cost optimization levers aligned with benchmark fuzzy sets. The fuzzy logic technique is efficient for optimization of business process variables offering effective resources when investigating variables that are not precise. A framework supporting uncertainty and vagueness of business process variables are considered. The research delivers a flexible thin slice decision-making framework of the solution with testing of cost optimization levers on business processes. This presents an overview of benchmark measures supporting enterprise practitioners relative to developing a cost optimization paradigm as an enhancement to the current design. An assessment framework effective in substantiating relationships between cost optimization levers, business processes, and corporate performance is developed.