Real-Time Data Utilization Barriers to Improving Production Performance: An In-depth Case Study Linking Lean Management and Industry 4.0 from a Learning Organization Perspective

Henrik Saabye,Brian Vejrum Wæhrens,Thomas Borup Kristensen

doi:10.3390/su12218757

Abstract

This study presents empirical evidence for the ongoing discussion about the link between Lean Management (LM) and industry 4.0 (I4.0) by exploring a non-technical perspective on how manufacturers can capitalize on their technological investments. The paper, therefore, studies the link between LM and I4.0 from a learning organization (LO) perspective by examining the implementation, commissioning, and utilization of a real-time operational data gathering system at a Danish building material manufacturer. This six months in-depth case study finds that for the manufacturer to utilize real-time operational data from a LO perspective, several barriers must be addressed: problem solving that is not initiated by operators, operators who do not have second-order problem-solving abilities, operators who perceive the new real-time data technology as coercive, poor learning environments and processes, and a lack of leadership that supports learning. This study can help practitioners understand the importance of balance, the prevalent technocentric focus when implementing new I4.0 technologies with a LO focus. Furthermore, the study provides practitioners with a list of specific barriers from a LO perspective to be mindful of when aiming to combine LM and I4.0 to improve production performance.

Highlights

I4.0 is presented as a promising set of integrated digital technologies to improve production performance significantly and bring manufacturing into the digital age [1]
We considered line management as a central group of informants since they, firstly, provided us with knowledge of the intentions and assumptions behind the decisions made about adopting lean management and new technology
Our scientific contribution is firstly to identify specific non-technological barriers that prevent manufactures from enabling their organization to explore and exploit real-time operational data from a learning organization (LO) perspective. We attain this by proposing a conceptual model (Figure 3) based on the theoretical notions of second-order problem solving [36], enabling formalization [29], fostering a supportive learning environment, and processes [31,32] and leadership that supports learning [19,31]

Summary

Introduction

I4.0 is presented as a promising set of integrated digital technologies to improve production performance significantly and bring manufacturing into the digital age [1]. By adopting I4.0 technologies, the manufactures can develop their production setup to potentially become both more effective and flexible in producing highly customized products on a large scale while still staying competitive regarding high productivity and continuously lowering costs per produced unit [4]. Manufacturers have invested many resources into acquiring these new I4.0 technologies to develop their productions system to be more flexible and productive [5]. When investing heavily in I4.0 technologies, the capital investment gets tied to the production machinery, and the depreciation cost of these investments is often quite irreversible and possesses low variability. Such investment poses financial risk if the technology is not successfully utilized [6]. To ensure full capitalization of manufactures’ I4.0 technology investments, the literature suggests implementation in conjunction with process excellence methodologies like Lean Management (LM) [7,8,9]

Methods

Results

Conclusion