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Data-driven Production Logistics

A value-oriented transition approach

Time: Wed 2023-12-13 10.00

Location: C1 , Kvarbergagatan 12, Södertälje

Video link:

Language: English

Subject area: Production Engineering

Doctoral student: Masoud Zafarzadeh , Produktionsutveckling

Opponent: Professor Martin Rudberg, Linköping University

Supervisor: Professor Magnus Wiktorsson, Skolan för industriell teknik och management (ITM); Universitets lektor Jannicke Baalsrud Hauge, Skolan för industriell teknik och management (ITM)

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In the current manufacturing environment, the constant evolution ofproducts and services creates complexities in managing the flow ofinformation. Production logistics (PL), as a vital element of manufacturingsystems, are highly influenced by these dynamics. Earlier research hasemphasised the need for seamless data flow from start to finish to cope withthese dynamics through digitalisation transition projects. However, earlierresearch argue that these projects are often technology-oriented and lack avalue-oriented perspective.Earlier research has indicated that digitalisation initiatives such asIndustry 4.0 emphasise the technological aspects of transitioning to a datadrivenfuture for production logistics. Thus, it is argued by earlier researchthat value creation is not solely technical but also socio-technical,highlighting the interplay between technology and social factors in shapingindustrial outcomes. Existing literature often overlooks the critical aspectof value orientation. This thesis contends that it is crucial for companies toadopt frameworks that guide the transition from data to value. Theseframeworks are designed to emphasise a value-oriented perspective, whichis particularly important when advancing towards data-driven productionlogistics.However, three major areas require further research. Firstly, it isimportant to understand the characteristics of a data-driven PL system.Secondly, there is an absence of tools or systematic methods to assess theflow of information in production logistics for the purpose of mapping valueand pinpointing waste resulting from data inefficiencies. Thirdly, it isnecessary to understand how to align data-driven solutions with the sociotechnicalenvironment and user-centric considerations.This thesis begins by identifying PL system requirements through asystematic literature review, case studies, and experiments, establishing asystematic foundation for value creation in the transition to data-driven PL.It also proposed a method for detection of waste on the shopfloor caused byinformation flow inefficiencies.The major contribution to the literature is the proposed framework forvalue-oriented transition to data-driven production logistics. Thisframework includes several findings of the thesis. The findings offerpractical tools for waste detection, digital service design, and acomprehensive framework for a value-oriented transition in data-drivenproduction logistics, providing valuable guidance to industry practitioners.