Abstract

Lean Engineering has come a long way from its first conception in the 1940s. What started as a production philosophy to enable manufacturing in Japan under severe resource constraints has developed into a globally adopted, widely aspired, often misinterpreted, and sometimes poorly understood, way and means of “doing business”. Short-sighted implementations of lean engineering in industrialized countries in a first wave in the 1970s were quickly accompanied by the slogan ‘lean is mean’ because of the focus on short-term financial gains at the expense of a complete understanding of the entire production and value chains. In a second wave in the 1990s, the focus of lean engineering implementations shifted to the core objective of lean engineering philosophies, the establishment of flow in the value chain through standardization. In parallel, Systems Engineering has continuously developed as a discipline which has moved away from the integration of components and subsystems, to the co-development of such units and building blocks of engineering and engineered products. This continued development of Systems Engineering as a discipline reflects the growing demand for systems thinking competency, to challenge the complexity of manufacturing and operations in an environment where product development, production and distribution is spread over large, not co-located teams on all continents. In this paper, the authors tie together the developments, tools and methodologies of Lean Engineering and Systems Engineering, and they show the growing similarity of both disciplines. In fact, these disciplines often describe the same effects, processes, and challenges in the workplace. The similarity has grown to a level where value streams in production or service delivery are analyzed and described in terms of one engineering discipline, while following methodologies and applying tools stemming from the other engineering discipline. The authors advocate that the debate should therefore not be over which engineering discipline to follow, but what tools and methodologies are most appropriate to enhance systems thinking competency, and to understand complexity in systems.

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