Presenting a Process Model of Lean Manufacturing in Industry 4.0 Based on a Mixed-Methods Research Approach

Abstract

This study aims to present a process model of lean manufacturing in Industry 4.0 based on a mixed-methods research approach. In terms of purpose, the study is applied, and in terms of data collection, it is classified as mixed-methods research (qualitative–quantitative). The statistical population in the qualitative section included university faculty members, experts in the fields of technology and manufacturing, as well as senior managers of production and research and development in the dairy industry. In the quantitative section, the population consisted of all managers and employees of the production and information technology departments of dairy manufacturing companies in Tehran. The sample size in the qualitative section was determined based on theoretical saturation (10 participants) using purposive sampling, while in the quantitative section, a sample of 361 participants was estimated using stratified random sampling. Data collection instruments included interviews in the qualitative section and a researcher-developed questionnaire in the quantitative section. The validity and reliability of the questionnaire were confirmed. Data analysis was conducted using SmartPLS 3 software. The results led to the identification of 28 components and 112 indicators. The variables of lean quality management, smart supply chain, lean process management, smart customer orientation, and smart human resources were considered as the core categories. The variables of technical factors, environmental factors, organizational factors, and operational factors were identified as causal conditions. The variables of employee competency, employee flexibility, employee knowledge management, and employee intelligence and awareness were identified as contextual conditions. The variables of internal uncertainty and competitors were considered as intervening conditions. The variables of financing, downsizing and mergers, employee empowerment, appropriate infrastructure, and the approval and modification of regulations were identified as strategies. Finally, the variables of cost reduction, increased productivity, just-in-time production and reduced production time, quality improvement, improved operational performance, mass customization, flexibility, and increased customer satisfaction were identified as outcomes.