A perceptual measure of the degree of development of proprietary equipment

In this article we evaluate the psychometric properties of a scale for a perceptual measure of the extent to which manufacturing organizations develop proprietary equipment. We use a confirmatory factor analysis (CFA) approach to assess unidimensionality and reliability as well as convergent, discriminant and concurrent validity. Convergent and discriminant validity is assessed using CFA of the multitrait-multimethod (MTMM) matrix. In addition, we assess the scale's factorial invariance across industries. Results suggest that although method effects are present, the scale demonstrates internal consistency and validity. Implications of this study in the field of operations strategy and general strategy are discussed

Performance Measurement in Sensorized Sociotechnical Manufacturing Environments

Part 4: Manufacturing Performance Management in Smart FactoriesInternational audienceIndustry 4.0 entails the digitization of the shopfloor operations combining technologies such as internet of things-enabled sensing, cyber-physical systems, data analytics, augmented reality, and wearable devices and robots that transform the manufacturing environment into a workplace of human-machine interactive symbiosis. With the digitization of the manufacturing environment, new opportunities emerge concerning performance measurement as new sources of real-time data become available, including data collated from the operator on the shopfloor. Traditionally, the human dimension had been disjoint from the situation analysis of shopfloor performance that drives evidence based decision making. This paper presents the features and advantages of performance measurement in human-workplace interactive manufacturing where detailed data on human performance is provided by sensors and utilized to improve the performance goals. The paper is concluded with a discussion on the impact of context information management for interactive manufacturing workplaces, as a means of delivering more informed situational awareness, a critical enabler for human-machine interaction, as well as for handling complexity in disparate data sources

Exploiting Lean Benefits Through Smart Manufacturing: A Comprehensive Perspective

Part 3: Cyber-Physical (IIoT) Technology Deployments in Smart Manufacturing SystemsInternational audienceLean Production has proven to be a valuable methodology to improve productivity while reducing costs. Notwithstanding the countless successful lean implementations in the extant literature, others highlight its limitations, especially in production environments characterized by demand volatility, high product mix and reduced lot sizes. Technology is seen by many as a potential solution to such limitations, especially in the last years, with Industry 4.0 becoming an emerging frontier for the smart factories of the future. However, studies about the relationship between lean and smart manufacturing are scarce and often anecdotal. Therefore, the proposed work aims to fill this gap by developing a comprehensive model that links these two perspectives and serves practitioners to achieve lean’s core goals in smart factories