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Developing decision-support tools for evaluation of manufacturing reshoring decisions
Jönköping University, School of Engineering, JTH, Industrial Product Development, Production and Design.ORCID iD: 0000-0002-1318-1598
2020 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

During last three decades, companies have offshored their manufacturing activities across international borders in order to pursue lower manufacturing costs. Despite having accomplished their purpose, companies have also suffered from issues, especially poor quality of products and a poor response to customer demand. Therefore, companies consider relocating some of the manufacturing activities back to the home country, a process that is known as manufacturing reshoring. There is paucity of scholarly attention on how manufacturing reshoring decisions are evaluated and supported. Therefore, the purpose of this thesis is to develop decision-support tools to evaluate manufacturing reshoring decisions. In order to fulfil this, it is important to know how industry experts reason while making manufacturing reshoring decisions (RQ1), and how their reasoning can be modeled into decision-support tools (RQ2). Therefore, three studies were conducted including a multiple case study and two modeling studies. The multiple case study addressed the criteria that are considered by the industry experts in these decisions, while the two modeling studies, based on fuzzy logic and analytical hierarchy process (AHP), used a part of these criteria to develop decision-support tools. The findings indicate that a holistic set of criteria were considered by industry experts in arriving at a manufacturing reshoring decision. A large portion of these criteria occur within competitive priority category and among them, high importance is given to quality, while low importance to sustainability. Fuzzy logic modeling was used to model the criteria from the perspective of competitive priority at an overall level. Three fuzzy logic concepts were developed to capture industry experts’ reasoning and facilitate modeling of manufacturing reshoring decisions. Furthermore, two configurations and sixteen settings were developed, of which, the best ones were identified. AHP-based tools were used to capture experts’ reasoning of the competitive priority criteria by comparing the criteria. It was observed that fuzzy logic-based tools are able to better emulate industry experts’ reasoning of manufacturing reshoring. This research contributes to theory with a holistic framework of reshoring decision criteria, and to practice with decision-support tools for evaluation of manufacturing reshoring decisions.

Abstract [sv]

Under de tre senaste decennierna har många företag flyttat sin produktion till lågkostnadsländer för att kunna utnyttja lägre lönekostnader. Många gånger har företagen genom denna åtgärd lyckats sänka sin tillverkningskostnad men samtidigt drabbats av oförutsedda problem kopplat till exempelvis produkt-kvalitet och möjligheten att kundanpassa produkter. Hanteringen av problemen har lett till ytterligare kostnader som många gånger överstigit besparingen i tillverkningskostnad. Detta har lett till att allt fler företag börjat flytta tillbaka sin produktion till hemlandet, så kallad reshoring. Reshoring är ett ungt område där det saknas forskning gällande bland annat hur den här typen av beslut på bästa sätt kan utvärderas och vilken typ av beslutstöd som kan underlätta den här typen av beslut. Därför är syftet med den här avhandlingen är att utveckla beslutsstödverktyg för utvärdering av reshoring beslut. För att uppfylla syftet har två forskningsfrågor formulerats. Den första frågan handlar om hur industriexperter resonerar kring reshoring beslut (RQ1) medan den andra frågan handlar om hur deras resonemang kan modelleras i beslutsstödverktyg (RQ2). Tre studier har genomförts för att besvara forskningsfrågorna, en fallstudie och två modelleringsstudier. Fallstudien fokuserar på att identifiera vilka kriterier som industriexperter beaktar medan modelleringsstudierna fokuserar på att utveckla beslutstödsverktyg där en del av dessa kriterier beaktas, med hjälp av fuzzy logic och analytical hierarchy process (AHP). Resultaten från forskningen visar att industriexperter bedömer reshoring beslut utifrån ett holistiskt perspektiv. En stor del av dessa beslutskriterier finns inom konkurrenskraft kategorin och inom dessa, har industriexperterna lagt högst vikt på kvalitet och lägst vikt på hållbarhet. Genom fuzzy logic modellering modellerades kriterierna på en övergripande nivå. Tre nya fuzzy logic koncept utvecklades för att fånga experternas resonemang. Dessutom utvecklades två konfigurationer med sexton olika inställningar, och de bästa identifierades. AHP-baserade verktyg utvecklades för att fånga experternas resonemang om kriterierna för konkurrenskraft prioriteringar. Fuzzy logic-baserade verktyg kan bättre fånga experternas resonemang kring reshoring beslut. Denna forskning bidrar till teori med en holistisk lista över beslutskriterier för reshoring beslut, och till praktik med beslutsstöd verktyg för utvärdering av reshoring beslut.

Place, publisher, year, edition, pages
Jönköping: Jönköping University, School of Engineering , 2020. , p. 69
Series
JTH Dissertation Series ; 054
Keywords [en]
Manufacturing reshoring, decision-making, support tools, fuzzy logic, AHP
Keywords [sv]
Produktion, reshoring, beslutsstödverktyg, fuzzy logik, AHP
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
URN: urn:nbn:se:hj:diva-48263ISBN: 978-91-87289-57-6 (print)OAI: oai:DiVA.org:hj-48263DiVA, id: diva2:1428198
Presentation
2020-05-26, da Vinci (jE4106) / via Zoom, Jönköping University, School of Engineering, Jönköping, 10:00 (English)
Opponent
Supervisors
Available from: 2020-05-05 Created: 2020-05-05 Last updated: 2020-05-05Bibliographically approved
List of papers
1. Criteria considered in a reshoring decision: a multiple case study
Open this publication in new window or tab >>Criteria considered in a reshoring decision: a multiple case study
(English)Manuscript (preprint) (Other academic)
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
urn:nbn:se:hj:diva-48259 (URN)
Note

Manuscript submitted for review (under review). An earlier version of this paper was submitted and accepted at the 9th Swedish Production Symposium (SPS), Jönköping, Sweden. 6-9 October 2020.

Available from: 2020-05-05 Created: 2020-05-05 Last updated: 2020-05-05
2. Three novel fuzzy logic concepts applied to reshoring decision-making
Open this publication in new window or tab >>Three novel fuzzy logic concepts applied to reshoring decision-making
2019 (English)In: Expert systems with applications, ISSN 0957-4174, E-ISSN 1873-6793, Vol. 126, p. 133-143Article in journal (Refereed) Published
Abstract [en]

This paper investigates the possibility of increasing the interpretability of fuzzy rules and reducing the complexity when designing fuzzy rules. To achieve this, three novel fuzzy logic concepts (i.e., relative linguistic labels, high-level rules and linguistic variable weights) were conceived and implemented in a fuzzy logic system for reshoring decision-making. The introduced concepts increase the interpretability of fuzzy rules and reduce the complexity when designing fuzzy rules while still providing accurate results.

Place, publisher, year, edition, pages
Elsevier, 2019
Keywords
Decision-making, Fuzzy logic, High-level rule, Linguistic variable weight, Relative linguistic label, Reshoring, Computer circuits, Decision making, Fuzzy inference, Fuzzy rules, Linguistics, Fuzzy logic system, High-level rules, Interpretability, Linguistic labels, Linguistic variable
National Category
Business Administration
Identifiers
urn:nbn:se:hj:diva-43403 (URN)10.1016/j.eswa.2019.02.018 (DOI)000464486100012 ()2-s2.0-85063033919 (Scopus ID)PP JTH 2019 embargo 24 (Local ID)PP JTH 2019 embargo 24 (Archive number)PP JTH 2019 embargo 24 (OAI)
Available from: 2019-04-01 Created: 2019-04-01 Last updated: 2020-05-05Bibliographically approved
3. Feasibility of fuzzy logic in reshoring decision making
Open this publication in new window or tab >>Feasibility of fuzzy logic in reshoring decision making
(English)Manuscript (preprint) (Other academic)
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
urn:nbn:se:hj:diva-48261 (URN)
Note

Manuscript submitted for review (under review). An earlier version of this paper was presented at the 9th International Conference on Operations and Supply Chain Management (OSCM), Ho Chi Minh City, Vietnam. 15-18 December 2019.

Available from: 2020-05-05 Created: 2020-05-05 Last updated: 2020-05-05
4. Feasibility of AHP support tools in reshoring decision making
Open this publication in new window or tab >>Feasibility of AHP support tools in reshoring decision making
(English)Manuscript (preprint) (Other academic)
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
urn:nbn:se:hj:diva-48262 (URN)
Note

Manuscript submitted for review (under review). An earlier version of this paper was presented at the 9th International Conference on Operations and Supply Chain Management (OSCM), Ho Chi Minh City, Vietnam. 15-18 December 2019.

Available from: 2020-05-05 Created: 2020-05-05 Last updated: 2020-05-05

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