Quantitative modelling approaches for lean manufacturing under uncertainty

[EN] Lean manufacturing (LM) applies different tools that help to eliminate waste as well as the opera-tions that do not add value to the product or processes to increase the value of each performedactivity. Here the main motivation is to study how quantitative modelling approaches can supportLM tools even under system and environment uncertainties. The main contributions of the articleare: (i) providing a systematic literature review of 99 works related to the modelling of uncertaintyin LM environments; (ii) proposing a methodology to classify the reviewed works; (iii) classifyingLM works under uncertainty; and (iv) identify quantitative models and their solution to deal withuncertainty in LM environments by identifying the main variables involved. Hence this article pro-vides a conceptual framework for future LM quantitative modelling under uncertainty as a guide foracademics, researchers and industrial practitioners. The main findings identify that LM under uncer-tainty has been empirically investigated mainly in the US, India and the UK in the automotive andaerospace manufacturing sectors using analytical and simulation models to minimise time and cost.Value stream mapping (VSM) and just in time (JIT) are the most used LM techniques to reduce wastein a context of system uncertainty.The research leading to these results received funding fromthe project 'Industrial Production and Logistics Optimizationin Industry 4.0' (i4OPT) (Ref. PROMETEO/2021/065) granted by the Valencian Regional Government; and grant PDC2022-133957-I00 funded by MCIN/AEI /10.13039/501100011033 and by European Union Next Generation EU/PRTR.Rojas, T.; Mula, J.; Sanchis, R. (2023). Quantitative modelling approaches for lean manufacturing under uncertainty. International Journal of Production Research. 1-27. https://doi.org/10.1080/00207543.2023.229313812

Modeling and analysing the barriers to the acceptance of energy-efficient appliances using an ISM-DEMATEL approach

Electricity savings from energy-efficient appliances (EEAs) may have a significant impact on reducing global warming. There are several barriers confronted by EEAs, which have lowered their acceptance rate. The current study identifies and highlights key barriers to strengthening domestic sector adoption of EEAs in developing countries. In the current study, thirteen barriers were discovered by an indepth literature review and the judgement of experts as well. Further, integrated “Interpretive Structural Modeling” (ISM) and “Decision Making Trial and Evaluation Laboratory” (DEMATEL) approaches are utilized to evaluate barriers. The ISM technique is implemented to categorize barriers into distinct hierarchy levels, and “Cross-Impact Matrix Multiplication Applied to Classification” (MICMAC) analysis to divide barriers among four clusters “independent, linkage, dependent, and autonomous”. Moreover, the DEMATEL methodology is applied to classify the barriers among cause and effect clusters. The integrated ISM and DEMATEL approach suggests that the topmost influencing barriers to the acceptance of EEAs are the lack of Government policies and initiatives, lack of attractive loan financing, and subsidized energy prices. This study would help researchers, regulators, producers, policymakers, and consumers to comprehend the need for additional developments and understand that the adoption of EEAs is a current need. Overall, the results of this study expedite stakeholders with the key barriers that may assist to enhance the acceptance of EEAs within the domestic sector. An extensive literature survey showed a dearth of studies for the identification, modeling, and analysis of barriers collectively. Therefore, the current work utilized the ISM and DEMATEL approaches to fill the gap and to provide more comprehensive knowledge on barriers related to the acceptance of EEA

Modeling the Critical Success Factors for BIM Implementation in Developing Countries: Sampling the Turkish AEC Industry

One of the latest advancements transforming the global architectural, engineering, and construction (AEC) industry is building information modeling (BIM). Although BIM implementation is at high level in developed countries, it is at a lower level in developing countries. BIM is new to the construction industry in Turkey, with only minor construction firms having implemented it. When making projections based on the current state of the Turkish AEC industry, it is foreseen that it will become mandatory in the near future. Considering this projection, it is doubtful that many construction companies will be caught unprepared for this situation and will not know how to implement BIM. Therefore, this study aimed to identify and model the critical success factors for BIM implementation and their impact size in order to gain insight for the fast and efficient implementation of BIM among construction firms in the Turkish AEC industry, which can be generalized for most developing countries. To reach these aims, a questionnaire was designed with 41 identified success criteria (SC) that were derived through a systematic literature review (SLR). The survey was conducted on construction professionals who actively implement BIM technology at their occupied firms in Turkey and they were asked to rank the importance of 41 SC on a five-point Likert scale. The sampling frame consisted of architects and civil engineers, and in total, 243 responses were received. The differentiation between SC and critical success criteria (CSC) was obtained by using a normalized mean cutoff value. An exploratory factor analysis (EFA) was used to identify the critical success factors (CSFs), and structural equation modeling (SEM) was used to examine the underlying size effects of each CSF on BIM implementation in the Turkish AEC industry. The results of this study reveal 20 CSC for successful BIM implementation, and EFA exhibited three CSFs from 20 CSC. Three critical success factors for BIM implementation in the Turkish construction industry were determined and grouped into two categories. “Awareness of technological benefits” and “organizational readiness and competitive advantages” formed one group and are the most influential critical success factors for BIM implementation. “Motivation of management regarding BIM” formed the second group of critical success factors that have a significant effect. © 2022 by the authors

Adoption of BIM by architectural firms in India: technology–organization–environment perspective

Building information modelling (BIM) is being heralded as a remarkable innovation in the built environment sector with expectations of lofty sector-wide improvements. Some countries have shown remarkable levels of uptake of BIM, along the way documenting some evidence of benefits stemming from BIM. However, countries such as India and China are late entrants in the BIM adoption journey and are seeing a slower adoption rate. This study develops a model using the technology–organization–environment framework to study the factors influencing BIM adoption by architectural firms in India and reasons for this slow adoption. The proposed model of BIM adoption is tested using the partial least square method against responses collected from 184 industry professionals based in India. Findings reveal that the adoption of BIM by Indian architectural firms is at the ‘experimentation’ stage with variables such as expertise, trialability, and management support exhibiting a strong positive influence on BIM adoption. The study also explains the status of BIM adoption in India with the help of a multi-level social construct, which places the level of BIM adoption in India between the micro- and meso-levels of organizational scales. Similarities and dissimilarities with previous findings are discussed in the paper to highlight the findings of this study. © 2016 Informa UK Limited, trading as Taylor & Francis Grou

Development of a modeling algorithm to predict lean implementation success

”Lean has become a common term and goal in organizations throughout the world. The approach of eliminating waste and continuous improvement may seem simple on the surface but can be more complex when it comes to implementation. Some firms implement lean with great success, getting complete organizational buy-in and realizing the efficiencies foundational to lean. Other organizations struggle to implement lean. Never able to get the buy-in or traction needed to really institute the sort of cultural change that is often needed to implement change. It would be beneficial to have a tool that organizations could use to assess their ability to implement lean, the degree to which they have implemented lean, and what specific areas they should focus on to improve their readiness or implementation level. This research investigates and proposes two methods for assessing lean implementation. The first is utilizing standard statistical regression. A regression model was developed that can be used to assess the implementation of lean within an organization. The second method is based in artificial intelligence. It utilizes an unsupervised learning algorithm to develop a training set corresponding to low, medium, and high implementation. This training set could then be used along with a supervised learning algorithm to dynamically monitor an organizations readiness or implementation level and make recommendations on areas to focus on to improve implementation success”--Abstract, page iv

A model for the relationship between user satisfaction of healthcare facilities management and core healtcare business

Public hospitals in Ghana, as in many other developing countries, are faced with facilities management (FM) challenges due partly to the problem of poor services and user dissatisfaction with FM service delivery. Studies to understand the relationship between user satisfaction of healthcare FM and core healthcare business have not addressed the issue from the perspective of this study. To fill this gap, the study examined the relationship between healthcare FM services based on the FM basic framework (people - patients, place – healthcare healing environment, processes –FM service quality and technology – quality of healthcare infrastructure and equipment) and core healthcare business (healthcare personnel, healthcare delivery, adequacy of healthcare resources and healthcare administrative process). The underlying theoretical frameworks for the study included the FM basic framework, SERVQUAL theory, Core Healthcare Business dimensions and A Staff and Patient Calibration Toolkit (ASPECT) which is based on a theory of supportive designs for healthcare facilities. Questionnaire was used to gather data from 622 patients of the three surveyed hospitals (Komfo Anokye, Cape-Coast and Tamale teaching hospitals) in Ghana. The data were statistically tested and analysed by structural equation modelling (SEM) technique. Twelve of the 19 hypotheses were supported. The findings showed that although the patients are satisfied with the quality of healthcare healing environment and the quality of healthcare infrastructure and equipment, they were dissatisfied with the FM service quality. Secondly, the results indicated that healthcare FM service quality and quality of healthcare infrastructure and equipment did not have a positive significant influence on the quality of healthcare administrative process. Also, the quality of healthcare healing environment did not show a positive significant influence on healthcare delivery. The quality of healthcare infrastructure and equipment also did not have a positive significant influence on healthcare personnel. Lastly, out of the four dimensions used to evaluate the quality of core healthcare business, patients were dissatisfied with the adequacy of healthcare resources and healthcare administrative process. Generally, the study model offered a good understanding of the factors that influenced the relationship between users (patients) satisfaction of healthcare FM and core healthcare business. The findings indicated that healthcare institutions must realize that quality healthcare FM service is a means for the healthcare organisations to stay relevant in the eyes of the patients. Thus, the study recommends that the surveyed teaching hospitals in Ghana should aim to achieve patient centered healthcare service deliver by effectively improving the quality of both their FM and core healthcare services, since patient satisfaction leads to patient loyalty

Design of flexible and adaptable healthcare buildings of the future: a BIM approach

The UK's Government Construction adviser announced that all the public construction will be implemented with BIM in the coming years. This decision affects dramatically the design phase of healthcare facilities as by 2016, BIM is mandatory in the implementation of the design process. Moreover, The UK Construction Strategy plan does not offer for investigating the multidisciplinary design space of possible solutions. The uncertainty that impacts on healthcare (demographic trends, changing patterns of disease, technological advances and clinical knowledge) has led healthcare policy makers to take action to manage demand for healthcare services and the supply enabled by healthcare infrastructure. A state of the art review of literature identified that healthcare facilities are not designed to be change-ready and that owners of such facilities have dynamic requirements. To future-proof healthcare facilities a design process is required to offer a collaborative, parametric lean construction practice that enables the design team to generate and analyse flexible healthcare building design spaces based on multi-stakeholder requirements. BIM and Integrated Project Delivery (IPD) offer dynamic decisions early in the design process. Here, IPD, the RIBA Outline Plan of Work 2012 and the BIM Guide from the Computer Integrated Construction Research Program were used to define the exact information exchange between the parties in a BIM-based construction process for change-ready healthcare facilities. A generic process map is derived from the literature for future testing and is presented in respect to the principles and philosophies of process protocol

Barriers in green lean implementation: a combined systematic literature review and interpretive structural modelling approach

Green Lean has recently emerged as an alternative strategy for organizations to pursue both operational and sustainability excellence. The interest on this approach has rapidly risen in both academic and industry circles. However, despite this interest, very limited research has focused on its implementation, and no research has investigated the barriers that hinder the success of such activity. This study investigates the Green Lean implementation barriers and their contextual relationships and effects on the integration and deployment of this approach. A Systematic Literature Review (SLR), Interpretative Structural Modelling and fuzzy Matriced’ Impacts Croise’s Multiplication Appliqée a UN Classement (MICMAC) analyzes were carried out. Fifteen barriers were extracted from the SLR and then validated in consultation with industry and academic experts. The Interpretive Structural Modelling (ISM) method was used to understand the relationship between the fifteen barriers and to develop a hierarchical model of these. The different barriers were classified into ‘linkage’ and ‘dependent’ barriers by using MICMAC analysis. The results suggested that all the identified barriers play an important role, and hence can equally act as a significant hurdle to the implementation of Green Lean projects. This study can help managers and policy makers in better understanding these barriers. Thus, they can be assisted in managing and prioritizing barriers towards the successful implementation of Green Lean initiatives for better financial and environmental performance.N/