Integration of Lean and Industry 4.0 for Smart Manufacturing

Abstract

The purpose of this study was to investigate the potential of integrating Industry 4.0 (I-4.0) technology with Lean Production (LP) systems to increase manufacturing productivity. LP has been in use for over four decades and has resulted in the development of a range of Lean tools and principles that have been proven effective in improving productivity and performance in different manufacturing sectors. However, since 2011, I-4.0 has also been increasingly utilized to enhance productivity. While both paradigms share the goal of enhancing productivity, Lean is a people-centered, while I-4.0 is a technology-centered approach. As a result, some researchers have raised concerns about the integration of I-4.0 into LP systems and the potential for a synergistic relationship between the two approaches. To analyze these concerns systematically, we conducted a Systematic Literature Review (SLR) investigating the relationship between Lean and I-4.0, identifying existing frameworks for combining the two, and identifying key factors that drive the successful integration of I-4.0 into LP systems. We also explored potential challenges that may arise during the integration process. The SLR findings revealed a lack of understanding of the relationship between Lean tools and I-4.0 technologies, particularly the one-to-one relationship. In addition, there is a lack of empirical studies exploring how these two paradigms can be integrated to enhance productivity. By addressing these gaps, we were motivated to conduct this dissertation research. The entire research work is divided into three studies. In the first study, we aimed to propose a conceptual framework for the successful integration of I-4.0 into the LP system. Besides the research gaps derived from the SLR in designing the framework, we employed basic principles of system thinking. The proposed framework is designed with a clear direction of the relationship between Lean and I-4.0, while also taking into account potential key driving factors and challenges. In the second study, we attempted to implement the proposed framework in a Lean Educational Automotive Manufacturing Lab. We demonstrated it as a small manufacturing floor to delineate the different phases of the proposed framework. To measure its performance, we defined the overall equipment effectiveness (OEE) as the primary key performance indicator (KPI). To explore the synergistic impact of Lean and I-4.0, we defined four treatments, namely `Control,' `Lean,' `Industry 4.0', and `Lean \& Industry 4.0'. In this study, 48 research subjects assembled SUV model cars using Lego parts to test the framework's performance based on the research protocol. The subjects assembled the cars individually under each treatment and also in combination. After conducting a comprehensive analysis, we found that the `Industry 4.0' approach resulted in significantly higher OEE compared to the other treatments. However, the study is limited to a small sample size. To overcome the limitation of a small sample size and to evaluate the effectiveness of workflow layout followed by subject, we were motivated to conduct the third study. In the third study, we explored whether the workflow layout impacts productivity or efficiency. To conduct our investigation, we randomly selected 12 research subjects to observe their performance during the car assembly process. We analyzed their performance based on recorded videos from our second study. Next, we created a discrete event simulation (DES) model to validate the observation using the empirical data of 12 research subjects. Through the observation, we found subjects followed eight different workflow sequences. Through the DES analysis, we discovered the significant impact of workflow on productivity and efficiency. In this study, we employed Throughput (TP) and Time In System (TIS) performance metrics to test our proposed hypotheses. Overall, it is worth mentioning that the study makes three contributions. Firstly, it presents a conceptual framework for integrating I-4.0 technologies into LP systems. Secondly, the performance of the proposed framework is validated by using human subjects in a prototype environment. Finally, effective utilization of DES in determining an efficient workflow sequence for picking and placing parts during the assembly of SUV cars.