Sustainable robust layout using Big Data approach: A key towards industry 4.0

A layout design based on large scale (Big) data is more efficient and effective in today's competitive market. Due to variations in product demands, varying product mix, and addition or deletion of products, layout of industry needs to be robust and sustainable. A robust and sustainable industry layout design is capable to handle the variations and is seen as first step towards Industry 4.0 to keep precise and accurate manufacturing of products in given due time. Poor layout design decreases the precision and accuracy in manufacturing of products and increases the production time. To design layout for Industry 4.0, this work proposes an embedded SA based meta-heuristic and principal component analysis (PCA) approach using large scale data to solve sustainable robust stochastic cellular facility layout problem (sustainable-RSCFLP). The data for the problem is collected considering basic 3Vs of Big Data i.e. Volume, Variety, and Velocity. Fourteen different criteria are identified and evaluated by 100 experts to group them based on their Eigen values using PCA. These are Distance, Adjacency, Shape ratio, Flexibility, Maintenance, Accessibility, Hazardous movement, Noise Level, Aesthetic, Safety, WIP and inventory, Space utilization, Capital equipment utilization, and Robustness. These fourteen criteria are clustered in to four factors using PCA approach. These clusters are defined as Material Handling Distance, Maintenance, Adjacency, and Hazard. The material handling distance comprises of three criteria such as Distance, Capital equipment utilization, and space utilization. In the same way, Maintenance comprises of three criteria such as Maintenance, Work in Process and inventory, and Accessibility. Similarly, Adjacency comprises of four criteria such as Shape ratio, Robustness, Adjacency, and Flexibility. Finally, Hazard comprises of four criteria such as Noise level, Aesthetics, Safety and Hazardous movement. In addition to these four clusters, fifth factor i.e. electrical energy consumption (EEC) is taken separately for each layout alternative to make the proposed layout environmentally sustainable. Thus, the proposed layout considers all pillars of sustainability i.e. EEC (maps environmental sustainability), Maintenance and Hazards (maps social sustainability), and Material Handling (maps economic sustainability) for designing cellular facility layout problem. Further, pool of layouts is generated using embedded SA based meta-heuristic. Each layout is evaluated over each clusters and EEC is calculated for each layout as to make the layout design sustainable. Furthermore layouts are ranked using TOPSIS, IRP, and weighted-IRP qualitative approaches, and a consensus ranking is finally provided to select an efficient sustainable robust layout for Industry 4.0.