Management of technology in the process industries: Matching market and machine

• Main Author: Samuelsson, Peter
• Format: Doctoral Thesis
• Language: English
• Published: KTH 2017
• Subjects: process industries; manufacturing; innovation; configuration; strategizing; capability; configuration modelling; production system; physical modelling; AOD; converter geometry; injection; mixing times; electric arc furnace; EAF; post-combustion; high-impedance; network disturbances; operational results
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-199705; http://nbn-resolving.de/urn:isbn:978-91-7729-256-2

The process industries span multiple industrial sectors and constitute a substantial part of the entire manufacturing industry. Since companies belonging to this family of industries are often very asset intensive, their ability to respond to changes is often limited in the short term. The adaptation of the capabilities of existing processes, and conversely finding products and market segments to match the production system capabilities, are an important part of product- and market development activities in the process industry. The importance to companies in the process industry of having a well-articulated manufacturing strategy congruent with the business strategy is second to none. However, to facilitate manufacturing strategy developments, it is essential to start with an improved characterization and understanding of the material transformation system. To that end an extensive set of variables was developed and related measures and scales were defined. The resulting configuration model, focusing on company generic process capabilities in the process industries, is to be regarded as a conceptual taxonomy and as a proposition available for further testing. The usability of the model was subsequently assessed using “mini-cases” in the forestry industry, where the respondents confirmed that the company’s overall strategy could benefit from this kind of platform as a possible avenue to follow. The model was deployed as an instrument in the profiling of company material transformation systems to facilitate the further development of companies' functional and business strategies. The use of company-generic production capabilities was studied in three case companies representing the mineral, food and steel industries. The model was found by the respondents to be usable as a knowledge platform to develop production strategies. In the final analysis of the research results, a new concept emerged called “production capability configuration": A process-industrial company’s alignment of its generic production capabilities in the areas of raw materials, process technology and products to improve the consistency among the variable elements that define operations and improve the congruence between operations and its environment. From the perspective of value creation and capture, firms must be able to manufacture products in a competitive cost structure within the framework of a proper business model. By using the configuration model, the relationship between manufacturing and innovation activities has been studied in the previously mentioned three case studies. In many cases the gap in capability appears as a limitation in the production system, requiring development efforts and sometimes investments to overcome. This is illustrated with two examples from the steel industry, where development efforts of the production system capabilities are initiated to better match the market demands. One example is the increase the volume- and product flexibility of an existing stainless steel melt shop, resulting in a proposed oblong Argon Oxygen Decarburisation (AOD) converter configuration that was subsequently verified using water modelling. The second example is from a carbon steel mill, where the target was to increase the raw material- and volume flexibility of another melt shop, by modifying the capabilities of the Electric Arc Furnace (EAF). Enabling EAF technologies are further described and evaluated using operational data and engineering type of estimates.  === <p>QC 20170116</p>