Contributions of lean six sigma to sustainable manufacturing requirements: an Industry 4.0 perspective

Titmarsh, Rohin; Assad, Fadi; Harrison, Robert

doi:10.1016/j.procir.2020.02.044

Cited by 42 publications

(15 citation statements)

References 16 publications

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“…In addition to other similar studies in this area [15][16][17], the critical success factors detected in this study regarding the implementation of digital Lean 6S are the following:…”

Section: Discussionsupporting

confidence: 53%

“…This leadership should lead to a digital model implementation for services and capital goods production and consumption, with high flexibility and real time interactions during production between machines, people and products [15,16]. The following statements can be highlighted regarding the application of Lean 6S and Industry 4.0 in a sustainable environment [17]:…”

Section: Introductionmentioning

confidence: 99%

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Adaptation of the Lean 6S Methodology in an Industrial Environment under Sustainability and Industry 4.0 Criteria

et al. 2021

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Industry 4.0 paradigms have a positive influence on standard operating procedures, methodologies used in Lean Manufacturing techniques and management models with sustainability criteria. Interdependencies and correlations have been found between Lean systems and Industry 4.0. The Lean principles of avoiding waste and zero defects are related to the cloud and big data paradigms. In a current workplace, there has been an exponential increase in digital information and the need to generate direct commitments to environmental management. This situation forces us to innovate and improve the management methodologies and models used in the industrial environment. The Lean 6S methodology must adapt and respond to new demands. In this work, an update of the Lean 6S methodology is carried out to guarantee increased productivity in the workplace through the organization of industrial resources, both physical and digital. A revision of the implementation procedure is proposed, which includes activities that generate a direct commitment to sustainability and the organization of digital information, through a proposal for an organizational architecture of Industry 4.0 technologies.

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“…In addition to other similar studies in this area [15][16][17], the critical success factors detected in this study regarding the implementation of digital Lean 6S are the following:…”

Section: Discussionsupporting

confidence: 53%

Section: Introductionmentioning

confidence: 99%

Adaptation of the Lean 6S Methodology in an Industrial Environment under Sustainability and Industry 4.0 Criteria

et al. 2021

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“…In the process, the adaptation, as well as the impact of the product on the surrounding living environment and living resources is the top concern, the green Six Sigma tool contributes to increasing the influence of the product in the living environment. Rohin Titmarsh et al (2020) proposed applying the Six Sigma cycle to the industrial 4.0 manufacturing environment based on information and communication technology to the Lean Six Sigma relationship in the DMAIC cycle (Srisuk & Tippayawong, 2020) to improve the machining process (Titmarsh et al, 2020). In the product processing process, fluctuation in the output of the process is the top concern, enterprises apply Six Sigma to the machining cycle to minimize the fluctuations in the output, which is realized through the processing cycle.…”

Section: Literature Reviewmentioning

confidence: 99%

Management and Production Engineering Review

Duc¹,

Bilík²

2022

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This paper proposes the application of the digital numerical control (DNC) technique to connect the smart meter to the inspection system and evaluate the total harmonic distortion (THD) value of power supply voltage in IEEE 519 standard by measuring the system. Experimental design by the Taguchi method is proposed to evaluate the compatibility factors to choose Urethane material as an alternative to SS400 material for roller fabrication at the machining center. Computer vision uses artificial intelligence (AI) technique to identify object iron color in distinguishing black for urethane material and white for SS400 material, color recognition results are evaluated by measuring system, system measurement is locked when the object of identification is white material SS400. Computer vision using AI technology is also used to recognize facial objects and control the layout of machining staff positions according to their respective skills. The results obtained after the study are that the surface scratches in the machining center are reduced from 100% to zero defects and the surface polishing process is eliminated, shortening production lead time, and reducing 2 employees. The total operating cost of the processing line decreased by 5785 USD per year. Minitab 18.0 software uses statistical model analysis, experimental design, and Taguchi technical analysis to evaluate the process and experimentally convert materials for roller production. MATLAB 2022a runs a computer vision model using artificial intelligence (AI) to recognize color objects to classify Urethane and SS400 materials and recognize the faces of people who control employee layout positions according to their respective skills.

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“…Although lean production minimises waste within the manufacturing process, Industry 4.0 aims to reduce waste for the organisation, including waste in the supply chain and within their customer network. Thus, to reach low-cost manufacturing efficiencies whilst also using automation, Lean 4.0 is focussed on new goals (Titmarsh et al , 2020; Ciano et al , 2021). A new system within the organisation places supply chain and material handling procedures side-by-side to form a lean manufacturing system that is flexible and efficient.…”

Section: Classical Strategies Of Lean 40 For Overall Enhancing the Ma...mentioning

confidence: 99%

Exploring relationships between Lean 4.0 and manufacturing industry

Javaid

Haleem

Singh

et al. 2021

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Purpose Over the past few decades, lean manufacturing has focussed on being customer-centred and now Lean 4.0 technologies have made it possible for manufacturers to have a deeper view of waste reduction. Technologies such as the internet of things, artificial intelligence, three-dimensional printing, robotics, real-time data, cloud computing, predictive analytics and augmented reality, are helpful to achieve Lean 4.0. This study aims to develop the conceptual understanding of Lean 4.0, related tools and linkage with Industry 4.0. Further, it provides the strategies for implementing Lean 4.0, developing lean culture and highlights the Lean 4.0 application in the manufacturing context. Design/methodology/approach This study relates to Lean 4.0 and its technologies. Prominent research is identified through Scopus, Web of Science, ScienceDirect and Google Scholar and studied as per the objective of this study. This lean revolution provides customers desire for personalisation, connectedness, high-quality and valuable products. Lean 4.0 provides valuable information on the value chain and production process. This revolution has significantly impacted refining production processes for a greater level of adaptability and cost reduction. Findings This paper is brief about Lean 4.0 and its capabilities for the reduction of waste. The authors discussed different tools used in Lean 4.0 and its relationship with Industry 4.0. The classical strategies and progressive features of Lean 4.0 for overall enhancing the manufacturing sphere are discussed diagrammatically. Finally, it identified and discussed 14 significant applications of Lean 4.0 for manufacturing industries. Originality/value This study provides a comprehensive understanding of Lean 4.0 and related tools and strategies that help the upcoming manufacturing industries.

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Contributions of lean six sigma to sustainable manufacturing requirements: an Industry 4.0 perspective

Cited by 42 publications

References 16 publications

Adaptation of the Lean 6S Methodology in an Industrial Environment under Sustainability and Industry 4.0 Criteria

Adaptation of the Lean 6S Methodology in an Industrial Environment under Sustainability and Industry 4.0 Criteria

Management and Production Engineering Review

Exploring relationships between Lean 4.0 and manufacturing industry

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