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1 – 6 of 6Daryl John Powell, Désirée A. Laubengaier, Guilherme Luz Tortorella, Henrik Saabye, Jiju Antony and Raffaella Cagliano
The purpose of this paper is to examine the digitalization of operational processes and activities in lean manufacturing firms and explore the associated learning implications…
Abstract
Purpose
The purpose of this paper is to examine the digitalization of operational processes and activities in lean manufacturing firms and explore the associated learning implications through the lens of cumulative capability theory.
Design/methodology/approach
Adopting a multiple-case design, we examine four cases of digitalization initiatives within lean manufacturing firms. We collected data through semi-structured interviews and direct observations during site visits.
Findings
The study uncovers the development of learning capabilities as a result of integrating lean and digitalization. We find that digitalization in lean manufacturing firms contributes to the development of both routinized and evolutionary learning capabilities in a cumulative fashion.
Originality/value
The study adds nuance to the limited theoretical understanding of the integration of lean and digitalization by showing how it cumulatively develops the learning capabilities of lean manufacturing firms. As such, the study supports the robustness of cumulative capability theory. We further contribute to research by offering empirical support for the cumulative nature of learning.
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Henrik Saabye and Daryl John Powell
This paper aims to investigate how manufacturers can foster insights and improvements from real-time data among shop-floor workers by developing organisational “learning-to-learn”…
Abstract
Purpose
This paper aims to investigate how manufacturers can foster insights and improvements from real-time data among shop-floor workers by developing organisational “learning-to-learn” capabilities based on both the lean- and action learning principle of learning through problem-solving. Second, the purpose is to extrapolate findings on how action learning can enable the complementarity between lean and industry 4.0.
Design/methodology/approach
An insider action research approach is adopted to investigate how manufacturers can enable their shop-floor workers to foster insights and improvements from real-time data at VELUX.
Findings
The findings report that enabling shop-floor workers to use real-time data consist of developing three consecutive organisational building blocks of learning-to-learn, learning-to-learn using real-time data and learning-to-learn generating real-time data − and helping others to learn (to learn).
Originality/value
First, the study contributes to theory and practice by demonstrating that a learning-to-learn capability is a core construct for manufacturers seeking to enable shop-floor workers to use real-time data-capturing systems to drive improvement. Second, the study outlines how lean and industry 4.0 complementarity can be enabled by action learning. Moreover, the study allows us to deduce six necessary conditions for enabling shop-floor workers to foster insights and improvements from real-time data.
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Anna Trubetskaya, Olivia McDermott, Pierre Durand and Daryl John Powell
This project aims to optimise a secondary agricultural company’s reporting and data lifecycle by providing self-help business intelligence at an optimal price point for all…
Abstract
Purpose
This project aims to optimise a secondary agricultural company’s reporting and data lifecycle by providing self-help business intelligence at an optimal price point for all business users.
Design/methodology/approach
A design for Lean Six Sigma approach utilising the define, measure analyse, design and verify methodology was utilised to design a new reporting and data product lifecycle.
Findings
The study found that this approach allowed a very structured delivery of a complex program. The various tools used assisted greatly in delivering results while balancing the needs of the team.
Practical implications
This study demonstrates how improving data analysis and enhanced intelligence reporting in agribusinesses enable better decision making and thus improves efficiencies so that the agribusiness can leverage the learnings.
Social implications
Improving data analysis increases efficiency and reduces agrifood food wastage thus improving sustainability and environmental impacts.
Originality/value
This paper proposes creating a standardised approach to deploying Six Sigma methodology to correct both the data provisioning lifecycle and the subsequent business intelligence reporting lifecycle. It is the first study to look at process optimisation across the agricultural industry’s entire data and business intelligence lifecycle.
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Anna Trubetskaya, Alan Ryan, Daryl John Powell and Connor Moore
Output from the Irish Dairy Industry has grown rapidly since the abolition of quotas in 2015, with processors investing heavily in capacity expansion to deal with the extra milk…
Abstract
Purpose
Output from the Irish Dairy Industry has grown rapidly since the abolition of quotas in 2015, with processors investing heavily in capacity expansion to deal with the extra milk volumes. Further capacity gains may be achieved by extending the processing season into the winter, a key enabler for which being the reduction of duration of the winter maintenance overhaul period. This paper aims to investigate if Lean Six Sigma tools and techniques can be used to enhance operational maintenance performance, thereby releasing additional processing capacity.
Design/methodology/approach
Combining the Six-Sigma Define, Measure, Analyse, Improve, Control (DMAIC) methodology and the structured approach of Turnaround Maintenance (TAM) widely used in process industries creates a novel hybrid model that promises substantial improvement in maintenance overhaul execution. This paper presents a case study applying the DMAIC/TAM model to Ireland’s largest dairy processing site to optimise the annual maintenance shutdown. The objective was to deliver a 30% reduction in the duration of the overhaul, enabling an extension of the processing season.
Findings
Application of the DMAIC/TAM hybrid resulted in process enhancements, employee engagement and a clear roadmap for the operations team. Project goals were delivered, and original objectives exceeded, resulting in €8.9m additional value to the business and a reduction of 36% in the duration of the overhaul.
Practical implications
The results demonstrate that the model provides a structure that promotes systematic working and a continuous improvement focus that can have substantial benefits for wider industry. Opportunities for further model refinement were identified and will enhance performance in subsequent overhauls.
Originality/value
To the best of the authors’ knowledge, this is the first time that the structure and tools of DMAIC and TAM have been combined into a hybrid methodology and applied in an Irish industrial setting.
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