Litcius/Paper detail

Smart manufacturing: a framework for managing performance

Shreyanshu Parhi, Kanchan Joshi, Milind Akarte

2020International Journal of Computer Integrated Manufacturing56 citationsDOI

Abstract

The research proposes a metric referred to as Smart Manufacturing Performance Measures (SMPMs), which are mapped with manufacturing decisions (structural and infrastructural) and manufacturing outputs (cost, quality, delivery, flexibility, and innovativeness). The mapping between manufacturing decisions, manufacturing outputs, and SMPMs, facilitates the organization in choosing SMPMs to deliver desired output as represented by the competitive priority. The approach provides a direction for the practitioners to implement and operate smart manufacturing systems efficiently and effectively by devising a performance measurement system. A total of 22 performance measures are identified through an in-depth literature review. These are further classified into hard and soft measures, which allow decision-makers to measure SMPMs and focus on a specific performance measure. Further, SMPMs is linked to 13 enablers, which are the driving technologies for implementing smart manufacturing systems. Smart manufacturing is evolving, and its implementation is still in the nascent phase. The proposed approach plays a vital role in redefining the manufacturing strategy while deploying smart manufacturing systems. The research contribution is a step-in assessment of smart manufacturing to understand the ‘what’ and ‘how’ of technological changes are transforming the operations and driving outputs.

Topics & Concepts

Flexibility (engineering)Smart manufacturingManufacturing engineeringComputer-integrated manufacturingAdvanced manufacturingComputer scienceIntegrated Computer-Aided ManufacturingMetric (unit)Quality (philosophy)Measure (data warehouse)Process development execution systemProcess managementSystems engineeringEngineeringOperations managementDatabaseMathematicsEpistemologyStatisticsPhilosophyDigital Transformation in IndustryEconomic and Technological Systems AnalysisBig Data and Business Intelligence