A comprehensive KPI network for the performance measurement and management in global production networks

Verhaelen, Bastian; Mayer, Frederik; Peukert, Sina; Lanza, Gisela

doi:10.1007/s11740-021-01041-7

Cited by 16 publications

(12 citation statements)

References 21 publications

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“…Göppert et al, 2021 An assembly control system based on Google Deep Mind's AlphaZero created, an ANN (Artificial neural networks) is incorporated into the approach that suggests favorable job routing decisions and predicts the value of actions. Verhaelen et al, 2021 A KPI network for global production networks is presented, which links the key figures of the site level and the corporate level. Aicha et al, 2021 An approach that combines two main metrics, which are the Quality Index and the Timing index, as criteria while selecting an optimal and feasible disassembly plan.…”

Section: Ladinig and Vastag 2021mentioning

confidence: 99%

Quality and Risk Management in Industrial Production Systems: A Literature Review

Baltag

Morariu

2022

Bulletin of the Polytechnic Institute of Iași. Machine Constructions Section

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Nowadays quality management and specific tools can represent a challenge in SMEs (small and medium enterprises). To assure the expected quality of the products, SPC (statistical process control) combined with industry 4.0 specifics offer instantaneous responses and triggers for needed actions. Therefore, risk analyses are used as enablers for quality-oriented behaviour, and risk mitigation and identification, together with collected data, represent a comprehensive system that leads enterprises to achieve the expected performance level needed to remain competitive in the market. In addition, risk management and quality management cannot be treated without looking at the maintenance activities and policies which can have a considerable impact on those two. This paper provides a comprehensive literature review of the papers from the quality management sector and articles where risk management and maintenance are seen as facilitators for quality improvement with an impact on the performance level. The main contribution of each paper is listed in the table which simplifies the reader’s access to the work done in the field and the overview presented enables easy access to trends in this field and offers a starting point for future research by presenting the gaps.

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Section: Ladinig and Vastag 2021mentioning

confidence: 99%

Quality and Risk Management in Industrial Production Systems: A Literature Review

Baltag

Morariu

2022

Bulletin of the Polytechnic Institute of Iași. Machine Constructions Section

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“…Hence, performance measurement systems (PMS) were introduced [7], which allows the visualization and analysis of the performance of the different processes [8]. In order to achieve a proper performance of such types of systems, it is necessary to define key performance indicators (KPIs) [9,10]. KPIs are, undoubtedly, the essential measurement and control tools within all the processes of an organization.…”

Section: Introductionmentioning

confidence: 99%

Key Performance Indicators Selection through an Analytic Network Process Model for Tooling and Die Industry

2021

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In the last few decades, the fast technological development has caused high competitiveness among companies, encouraging a pursuit for strategies that allow them to gain competitive advantage, such as the monitoring of performance by using key performance indicators (KPIs). However, its selection process is complex since there are several KPIs available to evaluate performance and different relationships between them. To overcome this challenge, the use of a multiple criteria decision-making model (MCDM) was proposed, namely the analytic network process (ANP) through which a reduced number of them are prioritized. To identify which KPIs are suitable for the press cast and die manufacturing industry, a literature review was made, and 58 unique KPIs were identified. Thus, to validate the proposed methodology, a case study was carried out in an automotive press molding industry. With the implementation of the proposed ANP model it was possible to identify 9 KPIs that ensure the correct molding process monitoring, while being aligned with the Balanced Scorecard criteria. The results show that the proposed model is suitable for selecting KPIs for the molding industry.

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“…Verhaelen et al [234] provide a method to evaluate new locations of factories in GPNs. Verhaelen et al [235] provide a framework of measures to evaluate the performance of GPNs. Verhaelen et al [208] provide a method to evaluate production ramp-up efficiency for SMEs in GPNs.…”

Section: Evaluation In Gpn Contextsmentioning

confidence: 99%

“…There is a deficit of decision support for the design and operation of GPNs [14]. Three separate, although interlinked, tasks of the core area have become a focus of attention in research because of an increasing industrial need for support to the complex tasks [14,227,235,256,257]. One critical task is the structural footprint design [258][259][260].…”

Section: Deficits and Propositionsmentioning

confidence: 99%

“…The impact of inferior decisions can be mitigated, and the cost and time efficiency of GPNs can be improved with a shift towards CMSs for a decisive competitive advantage [14,208,265]. The potential cost savings can be up to 45%, whereas most manufacturing firms only realize about 10% [122,133,235]. However, the evaluation of improvement potentials in GPNs is a challenge and lacks exploration in research [122,235,[274][275][276].…”

Section: Deficits and Propositionsmentioning

confidence: 99%

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Reconfigurable Manufacturing Systems in Global Production Networks

Kjeldgaard

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This PhD dissertation is the result of a three-year research project at the Department of Materials and Production at Aalborg University in close collaboration with Vestas Wind Systems A/S. The project is motivated by an industrial need and research deficit of methods and models for the financial evaluation of reconfigurable manufacturing systems in global production networks.The research project aims to support decision-making to advance a paradigm shift in the production domain that can enable efficient adaptability and resilience to uncertain changes. These capabilities are needed to secure a competitive advantage in the global wind energy industry. The fierce competition amongst firms increases the introduction rate of larger wind turbines for the onshore and offshore markets. Like the markets, the production is global across multiple factories and countries. Supply disruptions, transportation restrictions, and localization requirements pressure the firms to produce near the demand. However, the demand fluctuates on variety, volume, timing, and location, requiring the production mix of the factories to be adapted accordingly. This imposes frequent reinvestments in capital-intensive assets, which is further intensified when using dedicated manufacturing systems.ix ACKNOWLEDGMENTS I never believed I would complete a PhD project. I never even intended for university. Somehow, I find myself in this position. It required hard work, some luck, and, most of all, support from the people around me. I could not have done it without them.Firstly, I would like to thank my three supervisors, Thomas Ditlev Brunø, Ann-Louise Andersen, and Kjeld Nielsen. Without your support, advice, and guidance, I could not have managed the project. Ann-Louise, thank you for your encouragement to continue the PhD when I lacked belief. Thomas and Ann-Louise, thank you for forcing me to take a break when the pressure overwhelmed me. I would also like to thank Rasmus Andersen and Alessia Napoleone for the discussions and advice. A special thanks to my colleagues from Jönköping, Sweeden. Carin Rösiö, thank you for the opportunity to visit. Simon Boldt and Filip Skärin, thank you for our collaboration and friendship.Secondly, I would like to thank Vestas Wind Systems A/S, Manufacturing Academy of Denmark, and Innovation Fund Denmark for allowing me to conduct the research. My first industrial supervisor, Bjørn Christensen, thank you for opening the doors to Vestas and for your guidance. My second industrial supervisor, Mads Bejlegaard, thank you for picking me up, seeing my potential, and supporting my development. Michael Kofoed Dam, thank you for the warm welcome to the team and our field trips. Daniel Grud Hellerup Sørensen, thank you for the collaboration and advice. A special thanks to Henrik Espensen and Søren Damgaard for guiding me through the corporate maze and helping my work reach new heights up the corporate ladder.Last but not least, I would like to thank my family. The love of my life and fiancé, Aja Katrine Konnerup, thank you fo...

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A comprehensive KPI network for the performance measurement and management in global production networks

Cited by 16 publications

References 21 publications

Quality and Risk Management in Industrial Production Systems: A Literature Review

Quality and Risk Management in Industrial Production Systems: A Literature Review

Key Performance Indicators Selection through an Analytic Network Process Model for Tooling and Die Industry

Reconfigurable Manufacturing Systems in Global Production Networks

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