Leagile manufacturing: a review paper

Virmani, Naveen; Saha, Rajeev; Sahai, R.

doi:10.1504/ijpqm.2018.089807

Cited by 17 publications

(4 citation statements)

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“…However, the intricacies of operations have given rise to numerous challenges for industries. The key to staying competitive lies in enhancing productivity through optimal resource utilization and minimizing waste and defects in products and processes [20]. As such, Lean Six Sigma (LSS) has emerged as an integral approach for addressing dynamic customer requirements [21].…”

Section: Voc and Leanmentioning

confidence: 99%

A novel approach to voice of customer extraction using GPT-3.5 Turbo: linking advanced NLP and Lean Six Sigma 4.0

Shahin,

Chen,

Hosseinzadeh

et al. 2024

Int J Adv Manuf Technol

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This research breaks new ground by utilizing the advanced natural language processing (NLP) capabilities of OpenAI's GPT-3.5 Turbo model for the extraction of Voice of Customer (VoC) data from online customer support interactions on Twitter. Traditional methods of VoC extraction have typically fallen short in capturing the richness and nuance of customer sentiment. Contemporary Machine Learning (ML) approaches, while improved, still struggle to interpret the contextual subtleties of digital customer communications effectively. This study showcases the innovative deployment of GPT-3.5 Turbo, demonstrating its superior performance in extracting VoC through a deeper understanding of conversational context and a more intuitive, chat-based data processing. Furthermore, the large-scale, multilingual processing capabilities of this model offer a more comprehensive and inclusive analysis of VoC. The study ties these advancements to Lean Six Sigma 4.0, illustrating how the integration of GPT-3.5 Turbo's transformative capabilities can elevate the customer-centric approach of Lean Six Sigma in the era of Industry 4.0. This innovative exploration points to a signi cant evolution in VoC analysis, offering potential for more insightful, real-time data-driven customer service strategies and a more substantial foundation for decision-making in product development and process improvement. Future research is encouraged to validate these preliminary ndings and to investigate ethical considerations associated with the use of such advanced NLP models.

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Section: Voc and Leanmentioning

confidence: 99%

A novel approach to voice of customer extraction using GPT-3.5 Turbo: linking advanced NLP and Lean Six Sigma 4.0

Shahin,

Chen,

Hosseinzadeh

et al. 2024

Int J Adv Manuf Technol

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“…The need for social organizations to be able to combine exploitation and exploration is summed up in the term leagile. This is term is a portmanteau of the words lean and agile where lean maximizes efficiency in meeting stable demand while agile maximizes efficiency in meeting changing demand [61]. For example, many social organizations have to be able to explore how to survive in markets that change through new competitive forces.…”

Section: Survivalmentioning

confidence: 99%

Active Inference: Applicability to Different Types of Social Organization Explained through Reference to Industrial Engineering and Quality Management

Fox

2021

Entropy

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Active inference is a physics of life process theory of perception, action and learning that is applicable to natural and artificial agents. In this paper, active inference theory is related to different types of practice in social organization. Here, the term social organization is used to clarify that this paper does not encompass organization in biological systems. Rather, the paper addresses active inference in social organization that utilizes industrial engineering, quality management, and artificial intelligence alongside human intelligence. Social organization referred to in this paper can be in private companies, public institutions, other for-profit or not-for-profit organizations, and any combination of them. The relevance of active inference theory is explained in terms of variational free energy, prediction errors, generative models, and Markov blankets. Active inference theory is most relevant to the social organization of work that is highly repetitive. By contrast, there are more challenges involved in applying active inference theory for social organization of less repetitive endeavors such as one-of-a-kind projects. These challenges need to be addressed in order for active inference to provide a unifying framework for different types of social organization employing human and artificial intelligence.

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“…2.2 Agility in construction supply chain processes 2.2.1 Co-development of agile and lean management principles. Agile and lean management principles have co-existed for a long time and have been researched together in the context of construction management (Naim and Gosling, 2011;Virmani et al, 2018). Agile is understood as an ability to quickly respond to changes required by customers in an uncertain and changing environment (Owen and Koskela, 2006).…”

Section: Materials Flow Managementmentioning

confidence: 99%

Exploiting digitalization for the coordination of required changes to improve engineer-to-order materials flow management

Chen

Adey

Haas

et al. 2021

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Purpose The dynamic nature and complexity of construction projects make it challenging to ensure that the engineer-to-order (ETO) materials supplied onsite match changing needs. The quick and efficient communication of required changes in material fabrication, delivery and use, due to changes in the design and construction schedules, is needed to address the challenges. This study aims to provide a novel integrated management framework with its embedded informatics to help major stakeholders efficiently absorb agility during communication to deal with required changes and improve workflows. Design/methodology/approach An integrated management framework is developed that integrates the milestones in look-ahead plans and structured iterative processes for major supply chain stakeholders to quickly disseminate information emanating from changes in design, schedules, production and transportation. A prototype system is devised including the informatics to support the framework, which consists of BIM-RFID functional modules and a central database and uses a client-server architecture. The usefulness of the prototype is illustrated using a construction of part of a fictive but realistic high-rise building. Findings The integrated management framework with the informatics provides major stakeholders with the ability to coordinate their activities efficiently and stimulate their agility (measured by process time) in planning and controlling material information. Although only a fictive example was used, it is shown that the use of the system is likely to result in a substantial reduction in the time required to deal with required changes when delivering ETO materials onsite (by 18% in the example). Research limitations/implications The functionalities of the prototype system can be easily scaled up to coordinate changes in the design and scheduling of other types of materials. More functional developments are needed to show the extent of the possible improvement for entire construction projects. Future work should focus on investigating the possible improvements for other types and sizes of construction projects, and eventually in real-world construction projects. Practical implications By fitting the look-ahead plans into structured iterative processes through digital data sharing, stakeholders increased their capability to quickly capture required change information and resolve associated problems. This is particularly useful for the management of ETO supply chain processes, where prefabricated elements such as ductwork, plumbing, and mechanical systems typically have to be modified because of last-minute design and schedule changes. Originality/value Unlike traditional information technology (IT) based supply chain management practices, this research is characterized by a process-centered management framework that provides explicit decision points over iterative planning processes for major stakeholders to manage material information. The iterations through digital data sharing allow stakeholders to quickly respond to last-minute changes on site, which fundamentally achieves workflow agility in the construction supply chain context.

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Leagile manufacturing: a review paper

Cited by 17 publications

References 0 publications

A novel approach to voice of customer extraction using GPT-3.5 Turbo: linking advanced NLP and Lean Six Sigma 4.0

A novel approach to voice of customer extraction using GPT-3.5 Turbo: linking advanced NLP and Lean Six Sigma 4.0

Active Inference: Applicability to Different Types of Social Organization Explained through Reference to Industrial Engineering and Quality Management

Exploiting digitalization for the coordination of required changes to improve engineer-to-order materials flow management

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