Master thesis sponsored by funds from KTH Industrial Transformation Platform
KTH Industrial Transformation Platform sponsors project through the platform call. One of the project sponsored is the master thesis "Data-Driven Decision-Making for Sustainable Manufacturing Operations". Read about the project here.
Viktor and Arvid work is one of the first funded Master thesis projects by the KTH industrial transformation platform. As part of the platform network we are focusing on research to support the industrial transformation towards sustainable and CO2 neutral but also we look to strengthen collaboration between KTH researchers, in this case department of sustainable production development (HPU) and industrial engineering and Management (INDEK).
Students name: Viktor Nilsson & Arvid Westbroek, Master of Science at KTH Industrial Engineering and Management (INDEK)
Thesis title: Data-Driven Decision-Making for Sustainable Manufacturing Operations. An empirical study of supply chain operations within the Swedish manufacturing industry.
Academic Supervisor: Luca Urciuoli (INDEK)
Commissioner: Royal Institution of Technology
Contact persons: Zuhara Chavez and Mahesh Gopalakrishnan (HPU)
Data-Driven Decision-Making for Sustainable Manufacturing Operations
Currently, a digital transformation is reshaping the manufacturing industry, with new technologies such as artificial intelligence (AI), blockchain and big data leading the way. Such technologies are also allowing for data-driven processes, including decision-making. With data-driven decision-making, practitioners will not be depending on expertise and experience to make qualified decisions, rather they can make decisions based on more aspects than a human can manage as well as utilize real-time information. This would bring manufacturers to make more qualified operational decisions, nonetheless, covering more sustainability aspects.
In total, 14 in-depth interviews were conducted with both practitioners and experts, which led us to a holistic view of the Swedish manufacturing industry. When comparing the empirical information with previous literature, it was noted that data-driven decision-making entails both multiple challenges and advantages when it comes to improving manufacturers' sustainable performance. The main challenges include establishing efficient information sharing, standardized systems, and obtaining data that shows both reliability and validity.
By solving these challenges, the sustainable benefits can be met, including a mitigated bullwhip-effect, improved planning, and reduced CO2 emissions. These benefits are driven by the transparency, automatization, and optimization of processes that is incorporated with data-driven decision-making. In conclusion, realizing data-driven decision-making within the manufacturing industry brings several challenges, but if companies overcome the challenges the potential benefits will be unlimited.
Viktor Nilsson & Arvid Westbroek,
KTH Industrial Engineering and Management