Identification of Waste in Product Design Engineering - A case study of GE`s Oil & Gas engineering department in Stavanger
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The oil & gas industry, in their continuous pursuit to enhance product quality, and reduce time-to-market parameters simultaneously to achieve long-term success, is increasingly turning to the philosophy of Lean thinking. A philosophy heavily relied on the identification and removal of waste. GE Oil and Gas is one of the world`s leading companies providing advanced technologies and services to the oil and gas industry. In GE Oil & Gas Stavanger, product development projects, which is heavily influenced by knowledge work, are run in engineering departments using the traditional definitions of wastes established in the manufacturing environment. In order to run those projects more efficient, and continuously improve, tailored waste definitions for engineering waste is desired and needed. While there is a vast amount of literature investigating the traditional waste categories, or as defined in this study operational waste, few studies have looked at the notion of strategic waste. The academic purpose of this study is to increase knowledge of waste in both operational and strategic perspective, and their relationship. This is achieved by applying a mixed method approach, using quantitative and qualitative methods, where 1. Maturity assessment of survey data is used to prioritize the most critical and relevant operational waste in GE`s engineering department, and 2. Interviews, in form of 5 why`s analysis, are conducted to acquire additional in-depth knowledge of root-causes for the prioritized operational wastes. These are further discussed and categorized within the constructed theoretical concept of strategic waste, established in this study. The findings suggest that waste in product design engineering is difficult and complex to map. The challenges related to knowledge work is caused by several factors, and has several repercussions for the projects (Figure 13). The research identifies a number of relevant operational wastes in GE`s engineering department that should be further investigated (Table 8), but a handful were prioritized to conduct root-cause analysis on. The root-cause analyzes revealed a repeating pattern of causes and pre-conditions for the prioritized operational waste, which is possible to categorize within this study`s definition of strategic waste. The Table below lists the most critical and prioritized operational wastes in addition to their connecting strategic wastes.