Feasibility analyses of distributed digital factories over traditional factories: case studies and comparison

Purpose Many small and medium manufacturing companies face challenges with global competition due to limited access to advanced machinery and high overhead costs necessary to implement product-mandated line changes. To tackle this challenge, the concept of a distributed digital factory (DDF) has been proposed as compared to a traditional factory (TF). Design/methodology/approach This research used multiple case studies to identify potential issues and propose and validate solutions using DDF and TF in various manufacturing scenarios to address global challenges like cost reduction, productivity and flexibility to meet uncertain demands. Finally, queuing and simulation models were developed for feasibility analysis on isolated co-located factory environments and DDFs to reduce production lead time or improve customer response. The model identified DDF and TF variables, efficiency and correlations using global balance conditions to measure performance. Findings This paper theorized and researched four cases to determine manufacturing costs and capacity. DDF saved 9 and 14% as compared to TF in the first and second cases, respectively. Compared to traditional methods, DDF reduced queue time by 22.95 and 26.32% in two distributed factory facilities in the third case. In the fourth case, DDF handled 99% product demand situations and TF 28%. Originality/value This paper is the first paper that investigates and researches the specific factors and scenarios through which a DDF setup becomes more efficient, productive and cost-effective through several cases and sensitivity analysis.