Andreas Lugert, Aglaya Batz and Herwig Winkler
Value stream mapping (VSM) is very common in the manufacturing industry to enhance transparency and support improvements within the production process. The purpose of this paper…
Abstract
Purpose
Value stream mapping (VSM) is very common in the manufacturing industry to enhance transparency and support improvements within the production process. The purpose of this paper is to evaluate the current status of the method from the user’s point of view and addresses its future sustainability in the context of the ongoing digitalization.
Design/methodology/approach
An empirical survey with 170 participants from different branches was conducted. The web-based questionnaire covers the topics Lean Management, respectively, VSM, Industry 4.0, the integration of both approaches as well as a possible need for action to modify the VSM. Results are analyzed in a quantitative way.
Findings
Benefits and shortcomings of VSM are already confirmed by previous publications. The serious challenge is the lack of flexibility of the method. In general users appreciate a combination of Lean methods and solutions of Industry 4.0. Moreover 92 percent of the participating experts request further development of the VSM using digitalization to compensate weaknesses.
Research limitations/implications
The findings are based only on Lean expert’s opinion. Over 95 percent of the participants are from Europe however most of them are from Germany. Although the results are adequate an international expansion of the survey would be advisable in order to distinguish local differences and similarities. In future work researchers need to further develop VSM to overcome the identified gaps.
Practical implications
Results of the study indicate the viewpoint of experts within different branches. This enables users to undertake a self-assessment regarding their own VSM-estimation.
Originality/value
This paper provides a current evaluation of the VSM from an exploratory perspective. The impact of global trends and new opportunities facilitated by digitalization are considered. Shortcomings and fields of actions become clear. Based on that necessity further research activities can be designed.
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Moritz Berneis and Herwig Winkler
This study aims to explore the potential of blockchain technology in the field of supply chain management (SCM). The research is motivated by the emerging significance of…
Abstract
Purpose
This study aims to explore the potential of blockchain technology in the field of supply chain management (SCM). The research is motivated by the emerging significance of blockchain as a disruptive technology that can potentially address a range of challenges faced by SCM professionals globally.
Design/methodology/approach
In our approach, this paper utilized a knock-out criteria approach to break down 150 identified challenges in SCM to a more manageable number of 12. The Analytic Hierarchy Process (AHP) was then used to prioritize these challenges in order of their relative importance and suitability for resolution through blockchain.
Findings
The analysis identified key challenges to be addressed by blockchain technology in SCM. Most notably, it highlighted concerns related to price stability and global financial flows, which closely intertwine. Another significant group of issues pertains to tracking, tracing and the demonstration of sustainability, thus suggesting a substantial potential for blockchain application in these areas. The fifth notable challenge revolves around establishing ownership rights over digital assets or software.
Originality/value
This study identified key challenges in SCM with significant potential for blockchain intervention including price stability, global financial flows, tracking, tracing and the establishment of digital asset ownership. Research gaps exist despite notable progress in applications such as inflation control and tracking – especially in areas like ownership rights and e-commerce. The findings indicate that blockchain has the potential to address SCM challenges and that further exploration and implementation are necessary.
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Christian Stockmann, Herwig Winkler and Martin Kunath
The concept of robustness in manufacturing is not easy to capture and even harder to quantify. This paper elaborates an approach to assess robustness in production systems from a…
Abstract
Purpose
The concept of robustness in manufacturing is not easy to capture and even harder to quantify. This paper elaborates an approach to assess robustness in production systems from a holistic input-throughput-output perspective using a pragmatic robustness indicator.
Design/methodology/approach
First, in order to have a precise understanding of what needs to be measured, a concept of robustness in production systems is defined based on a literature overview. Three different aspects are considered to be essential to comprehensively describe robustness in production: the deviations of input resources, of performance and of output. These aspects are translated into an aggregated indicator based on developments of production costs, order delays and output volumes. The indicator-based assessment approach is eventually applied to a flow-shop scheduling case study in the chipboard industry.
Findings
The study shows that an assessment of robustness should not solely focus on a single aspect of a production system. Instead, a holistic view is required addressing the tradeoffs that robustness must balance, such as the one between the realized performance, the corresponding resource requirements and the resulting output. Furthermore, the study emphasizes that robustness can be interpreted as a superior system capability that builds upon flexibility, agility, resilience and resistance.
Research limitations/implications
First, the paper is a call to further test and validate the proposed approach in industry case studies. Second, the paper suggests a modified understanding of robustness in production systems in which not only the deviation of one single variable is of interest but also the behavior of the whole system.
Practical implications
The approach allows practitioners to pragmatically evaluate a production system’s robustness level while quickly identifying drivers, barriers and tradeoffs.
Originality/value
Compared to existing assessment approaches the proposed methodology is one of the first that evaluates robustness in production systems from a holistic input-throughput-output perspective highlighting the different tradeoffs that have to be balanced. It is based upon a comprehensive concept of robustness which also links robustness to adjacent capabilities that were otherwise only treated separately.
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Patrick Eichenseer and Herwig Winkler
With increasing demands for competitiveness, demand fulfilment and cost efficiency, the need to optimise workforce planning in logistics has become crucial. This applies not only…
Abstract
Purpose
With increasing demands for competitiveness, demand fulfilment and cost efficiency, the need to optimise workforce planning in logistics has become crucial. This applies not only to external customer demands, but also to internal customers, i.e. production. For this reason, the purpose of this paper is to develop a simulative, data-driven model that predicts the internal shopfloor material logistics demands.
Design/methodology/approach
It is a hybrid approach that includes both deterministic and probabilistic components and is an alternative to advanced but data and knowledge-dependent machine learning algorithms. Inductive, self-developed procedures, heuristic calculation rules and consideration of real-world factors form the basis of the prediction of the number of picks. The number of picks predicted in the first step forms the basis for deriving the number of employees required in the second step, and thus the basis for optimised workforce planning. The developed approach was then validated in a case study in a real company.
Findings
The results show that the model significantly optimises not only the planning efficiency, but also the forecasting effectiveness through better decision making in demand prediction and workforce planning in internal shopfloor material logistics compared to the status quo on a weekly basis (95.5% accuracy in the case study). This improved decision making leads to increased efficiency throughout the intralogistics/production system.
Originality/value
A structured approach is described for systematically predicting the number of internal picks, which is highly relevant in practice and cannot be found in the existing literature (from the data model to the calculation rules, including statistical influencing factors, to the prediction). In terms of future research, the model has the potential to be used and validated in additional companies.