Integrating Green Lean Six Sigma and industry 4.0: a conceptual framework

Kaswan M.S., Rathi R., Reyes J.A., Antony J.

The increased awareness about the effect of operations on sustainability dynamics and governmental pressure to cut emission rates has forced industries to adopt sustainable approaches such as Green Lean Six Sigma (GLSS). Despite increasing interest in GLSS, very limited research has focused on its implementation and no research has investigated barriers that hinder GLSS execution. This article investigates GLSS implementation barriers, their relationship, and removal of same in the manufacturing sector. In this article, 18 GLSS barriers have been recognized through literature review and formulated into logical groups using principal component analysis. This article pioneers with decision-making trial and evaluation laboratory with intuitionistic fuzzy (IF) set to prioritize barriers and handle the important and causal relationship among the same. The results of the article were validated through the IF best-worst method (BWM). The results reveal that management-related barriers are the top ranked followed by environmental and organization barriers with BWM weights 0.5283, 0.1704, and 0.1035, respectively. This provides impetus to policymakers for the induction of GLSS in business organizations to make harmony between economic development and environmental sustainability.

Karnik N., Bora U., Bhadri K., Kadambi P., Dhatrak P.

Since the first Industrial Revolution the trends in manufacturing have evolved a lot, from mechanical production to the era of smart manufacturing via technologies like Cyber Physical Systems, Internet of Things, Big Data, Cyber Security, Cloud Computing, Additive Manufacturing, Advanced robots, Modelling and Simulation and Augmented Virtual Reality. These technologies are enabling Interoperability and integration of various processes and departments in an organization because of the attribute of real-time inter-connectivity. Due to high inter-connectivity advantages like shorter development time, mass customization and modularity, configurability can be brought into existence. This will not only change the dynamics of the production lines but also add to the profit ratio of an organization by controlling over inventory via virtualization and predictive manufacturing. Due to such attributes of the Industry 4.0 paradigm, understanding them in depth is necessary. Hence, this paper aims to review many such characteristics, enablers, and main drivers of the Industry 4.0 paradigm and ultimately provides insight on the future scopes of each of the main pillars of Industry 4.0.

Rathi R., Kaswan M.S., Garza-Reyes J.A., Antony J., Cross J.

In the past few decades, a competitive landscape, learned customers and rigorous regulations have forced manufacturing industries to focus on sustainability alongside operational efficiency. The main objective of the present study is to develop a systematic Green Lean Six Sigma (GLSS) framework for improvement in operational efficiency together with environmental and social sustainability. Further, the proposed framework was tested in a leading manufacturing company. The framework was designed with insights gained from the literature and industrial personnel and encompasses the systematic application of different tools of the Green paradigm, Lean, and Six Sigma, from the identification and assessment of the problem to the sustainment of the adopted measures. A systematic application of lifecycle assessment and social lifecycle assessment was used to assess environmental and societal performance. The sustainability focused GLSS framework enhances the environmental capability, process performance and provides a new perspective for researchers and practitioners to support GLSS projects to achieving higher sustainability dynamics. • Green Lean Six Sigma (GLSS) sustainability oriented framework is proposed. • Lifecycle Assessment is deployed to assess environmental and social metrics. • Efficacy of GLSS tools has been tested at different steps of framework execution. • Proposed framework is tested in an industrial setting for sustainability improvement.

Siegel R., Antony J., Govindan K., Garza-Reyes J.A., Lameijer B., Samadhiya A.

Katoozian H., Zanjani M.K.

The manufacturing industry is confronted with the growing demand of personalized products of small batch sizes. In other words, the producers are faced with the satisfaction of heterogeneous customer needs through individualization and the realization of scale effects along the value chain. This study is among the first that proposes a mixed-integer programming model to obtain the optimal configuration of a supply network comprising of a pool of suppliers to satisfy the demand of highly-customized and modular-structured products. The product individualization is incorporated into the model by considering different design complexity levels for the components/sub-assemblies in the bill-of-material. Furthermore, the impact of batch size is modeled by considering piece-wise production cost functions in different echelons of the network. Our numerical results inspired by the case of tunable lasers indicate that the configuration of supply network varies as a function of the demand at different design complexity levels. Whereas, the profitability of supply network is closely tied to the market condition as well as the production capacity, flexibility of processes, and cost structure of manufacturers.

Yilmaz A., Dora M., Hezarkhani B., Kumar M.

Manufacturing companies have started to embrace Industry 4.0 and lean principles to stay competitive. However, the real industry implementation of the integrated approach has been challenging. Even separately, both Lean and Industry 4.0 have high failure rates. Understanding these implementations is essential to increase the application's success and build a bridge between academia and industry. This research uses a systematic literature review methodology to identify case studies that integrate the implementation of lean principles with Industry 4.0 technology. The benefits, barriers, and success factors of the integration were investigated, focusing on environmental, social, and operational perspectives. Forty-two case studies that included lean principles and Industry 4.0 technology in the manufacturing context were identified. The integration resulted in various operational benefits regarding lead-time, throughput, and quality. In terms of environmental impact, there is a potential to estimate the use of resources involved in the production and reduce CO2 emissions. Other benefits include improved employee welfare, better communication, employee empowerment. The main barrier is the investment cost followed by technological readiness. It has been concluded that Lean and Industry 4.0 present considerable potential. However, the integration needs proper understanding on how to start, where to aim, what to be aware of.

Surange V.G., Bokade S.U., Singh A.K., Teli S.N.

To experience seamless adoption of future industry 4.0, it is imperative to investigate its existing roadblocks and success factors in the Indian manufacturing context. Striking similarities among diverse researches highlight the importance of the cyber-physical system assuring many benefits to the manufacturing sector. Many studies concluded that sooner or later, all manufacturing companies will evolve by penetrating industry 4.0 technologies in their enterprise activities. There is a possibility of negative consequences on business functions if top management remains unprepared to assess roadblocks to these future technologies' adoption. Identification of roadblocks is the first and foremost thing industrial policymakers should focus on. This research enlists the stumbling blocks for industry 4.0 technologies' adoption that manufacturing industries may encounter by reviewing the latest literature and ranks them using VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methodology by consulting five experienced Indian industrial authorities. Weightage to each industrial experts' input is decided by the entropy method. Results indicate that “Skilled workers scarcity,” “Internal employee resistance,” “Worries about cyber security,” and “Inadequate knowledge of/from exterior agencies” are the top four barriers to the incorporation of industry 4.0 technologies in the Indian manufacturing context while “Lack of knowledge about enabling technology solutions” secured lower position. The robustness of the output was checked by carrying out a sensitivity analysis with varying weights. The approach adopted in this study will be helpful for industrial authorities to concentrate their efforts in tackling the most critical barriers. This research will aid industrial decision-makers in remaining proactive during the industrial technology adoption transition.

Belhadi A., Kamble S.S., Gunasekaran A., Zkik K., M. D.K., Touriki F.E.

The advent of new technologies alongside the generation of the vast amount of data in the manufacturing processes makes Green Lean Six Sigma (GLSS) approaches very challenging. This paper presents ...

Beltrami M., Orzes G., Sarkis J., Sartor M.

Both Industry 4.0 and sustainability have gained momentum in the academic, managerial and policy debate. Despite the relevance of the topics, the relation between Industry 4.0 and sustainability – revealed by many authors – is still unclear; literature is fragmented. This paper seeks to overcome this limit by developing a systematic literature review of 117 peer-reviewed journal articles. After descriptive and content analyses, the work presents a conceptualization and theoretical framework. The paper contributes to both theory and practice by advancing current understanding of Industry 4.0 and sustainability, especially the impact of Industry 4.0 technologies on sustainability practices and performance.

Chiarini A., Kumar M.

The purpose of this paper is to contribute to the scientific debate on Quality 4.0 by exploring the main theoretical themes underpinning the Quality 4.0 model and how the model may be developed. An...

Kaswan M.S., Rathi R., Singh M., Garza-Reyes J.A., Antony J.

Purpose The increased health-care costs, improved service quality and sustainability-oriented customer demand have forced the health-care sector to relook their current process. The present work deals with the identification, analysis and prioritization of just in time (JIT) enablers in the health-care sector. Design/methodology/approach JIT leads to waste reduction, improves productivity and provides high-quality patient care. The practical implementation of JIT depends on vital factors known as enablers. The enablers have been found through the comprehensive literature review and prioritized using responses from different health-care facilities of the national capital region of India. Grey relational analysis (GRA) has been used in the present study to rank enablers and ranks were further validated using the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) and sensitivity analysis. Findings It has been found that top management support, teamwork and real-time information sharing are the most significant enablers of JIT in health care with grey relational grades 0.956, 0.832 and 0.718, respectively. The corresponding closeness coefficients of the fuzzy TOPSIS for the enablers were found as 0.875, 0.802 and 0.688, respectively. The findings of the present research work will facilitate the health-care organizations to implement a comprehensive JIT approach that further leads to improved patient care at a low cost. Originality/value The present study is unique in terms of the exploration of the readiness measures or enablers of JIT using GRA and fuzzy TOPSIS. The findings of the present research work will facilitate the health-care organizations to optimize their resources for better patient care.

Kumar S., Raut R.D., Nayal K., Kraus S., Yadav V.S., Narkhede B.E.

With increasing globalization and digitalization, agricultural organizations have started changing their business processes. Agri-organization has begun to adopt technologies to get a more sophisticated, customer-centric, and sustainable supply chain. Although the introduction of interconnected new technologies and the concept of circular economy (CE) present numerous challenges, it has proved its value in the industrial sector to achieve a sustainability target. This study identifies Industry 4.0 (I4.0) and CE adoption barriers in the agriculture supply chain (ASC) in India. The study was extended to ascertain the contextual relationship among the barriers and to prioritize them with respect to one another. The 11 barriers with their key elements were enlisted after thorough literature analysis and interaction with experts. The barriers were modeled through an integrated ISM-ANP approach. The study indicates that lack of government support and incentives and lack of policies and protocols are significant obstacles to implementing the I4.0-CE model. The findings of the current research work will be beneficial for the agri supply chain stakeholders in preparing the strategic deployment of I4.0-CE. • The environmental and sustainability issues are pushing the agricultural supply chain players to implement modern technologies. • Numerous challenges in implementing and integrating the circular economy and Industry 4.0 practices in the agricultural supply chain. • Lack of government support and incentives for sustainability. • Lack of policies and protocol are the significant barriers for the agricultural supply chain organization. • Short, medium- and long-term strategic planning would help the practitioner adopt the circular economy and Industry 4.0.

Krishnan S., Gupta S., Kaliyan M., Kumar V., Garza-Reyes J.A.

PurposeThe aim of this research is to assess the key enablers of Industry 4.0 (I4.0) in the context of the Indian automobile industry. It is done to apprehend their comparative effect on executing I4.0 concepts and technology in manufacturing industries, in a developing country context. The progression to I4.0 grants the opportunity for manufacturers to harness the benefits of this industry generation.Design/methodology/approachThe literature related to I4.0 has been reviewed for the identification of key enablers of I4.0. The enablers were further verified by academic professionals. Additionally, key executive insights had been revealed by using interpretive structural modelling (ISM) model for the vital enablers unique to the Indian scenario. The authors have also applied MICMAC analysis to group the enablers of I4.0.FindingsThe analysis of this study’s data from respondents using ISM provided us with seven levels of enabler framework. This study adds to the existing literature on I4.0 enablers and findings highlight the specificities of the territories in India context. The results show that top management is the major enabler to I4.0 implementation. Infact, it occupies the 7th layer of the ISM framework. Subsequently, government policies enable substantial support to develop smart factories in India.Practical implicationsThe findings of this work provide implementers of I4.0 in the automobile industry in the form of a robust framework. This framework can be followed by the automobile sector in enhancing their competency in the competitive market and ultimately provide a positive outcome for the Indian economic development led by these businesses. Furthermore, this work will guide decision-makers in enabling strategic integration of I4.0, opening doors for the development of new business opportunities as well.Originality/valueThe study proposes a framework for Indian automobile industries. The automobile sector was chosen for this study as it covers a large percentage of the market share of the manufacturing industry in India. The existing literature does not address the broader picture of I4.0 and most papers do not provide validation of the data collected. This study thus addresses this research gap.

Kumar P., Bhamu J., Sangwan K.S.

Industry 4.0 has enabled technological integration of cyber physical systems and internet based communication in manufacturing value creation processes. As of now, many people use it as a collective term for advanced technologies, i.e. advanced robotics, artificial intelligence, machine learning, big data analytics, cloud computing, smart sensors, internet of things, augmented reality, etc. This substantially improves flexibility, quality, productivity, cost, and customer satisfaction by transforming existing centralized manufacturing systems towards digital and decentralized one. Despite having potential benefits of industry 4.0, the organizations are facing typical obstacles and challenges in adopting new technologies and successful implementation in their business models. This paper aims to identify potential barriers which may hinder the implementation of industry 4.0 in manufacturing organizations. The identified barriers, through comprehensive literature review and on the basis of opinions collected from industry experts, are: poor value-chain integration, cyber-security challenges, uncertainty about economic benefits, lack of adequate skills in workforce, high investment requirements, lack of infrastructure, jobs disruptions, challenges in data management and data quality, lack of secure standards and norms, and resistance to change. Interpretive Structural Modeling (ISM) is used to establish relationships among these barriers to develop a hierarchical model and MICMAC analysis for further classification of identified barriers for better understanding. An analysis of driving and dependence of the barriers may help in clear understanding of these for successful implementation of Industry 4.0 practices in the organizations.

Ershadi M.J., Qhanadi Taghizadeh O., Hadji Molana S.M.

Nowadays budget and schedule constraints have forced organizations to select six sigma projects based on pre-defined success criteria. Also, progressive approaches based on green and lean paradigm are vital for companies to enhance their social and environmental performance. Then, Green Lean Six Sigma (GLS) projects play the main role in improving the performance of an organization while augmenting its sustainability. Accordingly in this paper, past studies were reviewed, and GLS projects’ indicators and performance evaluation criteria were identified. Data envelopment analysis (DEA) was employed for the appropriate selection of GLS projects. Next, the ranking and performance weight of each project were investigated, and also the projects were categorized based on the technology readiness level (TRL). Additionally, an adaptive neuro-fuzzy inference system (ANFIS) method was applied for the successful prediction of selected GLS projects. Twenty-eight inputs and 9 outputs for the first project category (with TRL 9) and 28 inputs and 6 outputs for the second project category (with TRL 8) were entered into the model. The statistical assessment measures such as Nash–Sutcliffe efficiency (NSE), root mean squared of error (RMSE), mean absolute error (MAE), and R2 were employed for capability appraisal of ANFIS model. Results of NSE and R2 indicators for both project categories were 1.00 that proved the efficiency of the ANFIS model for success prediction of GLS projects. Also, RMSE and MAE indicators for category 1 were 0.01 and 0.02 respectively. Similarly, these measures for category 2 were 0.02 and 0.02. The results advocate a proper approximation for observed values by the ANFIS model. Also, the results indicated that TRL as an important enabler of the GLS project has a meaningful role in the performance of GLS projects.

Virmani N., Mahajan A., Jagtap S., Mahajan R.

Ibrahim A., Kumar G.

The relationship between Lean Six Sigma, Industry 4.0 and sustainable manufacturing has been evaluated only to a limited extent within this domain of the published literature. A DMAIC-DMADV-based framework along with a phase-by-phase implementation path is proposed in this study to integrate Lean Six Sigma and Industry 4.0 technologies for achieving sustainable manufacturing. The paper also focused on identifying and prioritizing the critical success factors for the implementation of the proposed framework. The critical success factors identified through a literature review are ranked using the multi-decision criteria technique TOPSIS, with input from selected experts across various manufacturing companies. The results highlight that the most important enablers set clear sustainability goals, regularly monitor progress and have a skilled workforce. The findings provide actionable guidance for practitioners, and the study contributes to the existing body of knowledge by offering a comprehensive methodology to integrate Lean Six Sigma and Industry 4.0 for sustainable manufacturing. Further research must focus on the validation of the framework in diverse industrial settings and refining the sustainability assessment model to enhance its adaptability.

Shabur M.A.

This research is designed to understand the concept of digital economy and its sustainability. These facts and concepts have gained popularity as a result of the growing concern about climate change and the advancement and acceptance of technologies. Scholars, corporate executives, and policymakers are investigating the various ways in which digital innovations may be utilized to tackle sustainability challenges. Through a rigorous literature review and bibliometric assessment, we examined a subset of 116 works cataloged in SCOPUS to assess the research on this subject from 2000 to November 2023. Our study revealed that the year 2022 featured the highest number of peer-reviewed publications, with a total of 31 publications. During our study, we have identified many potential avenues for this interconnection, such as the progress of energy sources that are renewable and sustainable technological advances, the development of technologically advanced cities and environmentally-friendly growing urbanization, and the encouragement of sustainable consumer behavior. Digital technology provides firms with chances to implement sustainable business approaches and create sustainable goods. Although the digital economy offers several benefits, it also poses some obstacles that might impede progress toward sustainability objectives. These challenges include the escalation of electronic waste, excessive energy usage and the subsequent increase in greenhouse gas emissions, technological division, employment instability, the growth of monopolies, and concerns over data privacy. In order to fully capitalize on the potential offered by the electronic economy to advance sustainability, it is imperative to tackle these challenges.

Raihan A.

Muniapan K., Ahmad R., Jusoh M.S., Mustafa S.A., Sin T.C.

PurposeThis paper proposes an assessment method for lean and sustainability (LS) practices for shop-floor workers, designed to evaluate their current practice culture.Design/methodology/approachThe method is developed in five phases: setting predefined indicators, constructing the assessment mechanism, implementing the assessment procedure, analyzing data and delivering results with recommendations. Validation is performed using two worker groups – line supervisors and operators – within the light-emitting diode (LED) manufacturing industry.FindingsThe results showed that workers’ familiarity and understanding of LS practices do not always correspond to their awareness levels. Key recommendations include prioritizing training for critical cases and adapting training approaches to fit the specific knowledge profiles identified.Research limitations/implicationsFirstly, the company should integrate the proposed assessment into an online platform that can automatically generate individual statistical results and priority levels. This reduces the burden of manual work and makes large-scale assessments more practical. Secondly, the study should expand to other shop-floor workers, such as technicians and engineers, to assess their knowledge profiles for future LS development initiatives.Practical implicationsThe recommendations provide managers and training departments with guidelines to revise current training approaches. The methodology is validated, enabling the identification and mapping of each worker’s knowledge profile.Originality/valueThis study presents an original assessment method for evaluating the knowledge profiles of shop-floor workers regarding LS practices. To the best of the authors’ knowledge, no prior literature has reported on an assessment method targeting this specific group. The proposed approach supports the decision-making process for better LS practices in the company.

Ozkan-Ozen Y.D., Garza-Reyes J.A., Kazancoglu Y.

Kumar R., Kumar R., Kumar A.

In the era of Industry 4.0, the Lean Green approach stands as a beacon of environmental sustainability and waste reduction within manufacturing processes. This study delves into its implementation dynamics within the Indian manufacturing landscape. Employing a comprehensive methodology, a widespread questionnaire survey was conducted across companies to gauge and rank barriers hindering seamless integration. The analytical framework, structured around a three-tier hierarchy diagram, leveraged the Analytical Hierarchy Process (AHP), a renowned Multi-Criteria Decision Making (MCDM) technique. Through this systematic approach, insights were gained into pivotal barriers, with employee motivation emerging as the linchpin for driving Lean Green initiatives. Lack of motivation surfaced as the most salient barrier, significantly impacting operational efficacy. These findings underscore the critical importance of addressing motivational factors to propel sustainable manufacturing practices amidst Industry 4.0 advancements.

Channi H.K., Kumar P., Dhingra A.

Kaswan M.S., Chaudhary R., Garza-Reyes J.A., Singh A.

PurposeThe purpose of this study is to review the different facets associated with Industry 5.0 (I5.0) and propose a conceptual framework to boost the applicability of this novel technological cum social aspects within industrial organizations for improved organizational sustainability.Design/methodology/approachThis research work adopted a bibliometric analysis that encapsulates a quantitative set of tools for bibliometric and bibliographic information. This study uses the database of Scopus to acquire data related to different facets of I5.0. The study implies a different spectrum of terms to reach the final corpus of 91 articles related to I5.0. Furthermore, a conceptual define, measure, analyze, improve and control (DMAIC)-based framework based on different literature findings is proposed and validated based on the input of experts from different parts of the world.FindingsThe results indicate that I5.0 is still in its infancy. The wider applicability of I5.0 demands comprehensive theoretical knowledge of different facets of this new paradigm and the development of a framework to adopt it on a larger scale. Organizations that are in the race to adopt I5.0 face major challenges related to the digitization of processes along with well-defined cyber-physical systems and the lack of a dedicated framework to execute I5.0. Furthermore, the result also suggests that manufacturing industries are more ready to adopt I5.0 practices as compared to service industries, which can be attributed to well-defined technological measures available in manufacturing settings.Originality/valueTo the best of the authors’ knowledge, this is one of the first studies that explore different know-how and challenges and provides a holistic view of I5.0 by providing a systematic adoption framework.

Gholami H., Lee J.K., Garza-Reyes J.A., Salameh A.A.

PurposeSince the advent of Industry 4.0, there has been a growing research interest in developing the Green Lean Six Sigma concept in the direction of achieving sustainable development, primarily aligned with Goal 12 of the agenda. Given that the concept is still in its early stages of exploration and requires further development through empirical validation, opportunities exist for innovative research. Yet, difficulties arise in adopting this green initiative due to an inadequate understanding of its strategic practices. Thus, this study aims to establish strategic practices facilitating its adoption in the Industry 4.0 era and develop a validated multi-item scale to measure the practices.Design/methodology/approachA three-phase methodological approach is designed to perform the techniques of exploratory and confirmatory analyses in the manufacturing context. To be a sound study, engineers have been involved since they play a pivotal role in the realm of manufacturing; however, the existing research on engineers' viewpoints on this subject is limited, emphasizing the need for further investigation.FindingsUpon validation of the ultimate fallouts, the analyses demonstrated a confirmatory model with eighteen scales determining five practices: strategic integrity, human resource management, technologies and tools, eco-production, and eco-networks. The findings further revealed robust correlations among these core practices within the model.Originality/valueThe contribution of this study entails depicting and discussing a measurement model for future research since there is currently no empirically validated model available to measure this multidimensional green initiative.

Kumar M., Vipin, Agarwal A.

Duarte S., Mc Dermott O.

Jin H., Qu P., Zhou Y., Qu Q., Li H.

Kokkinou A., van Kollenburg T., Mathijssen G., Vissers E., van Doren S.

Purpose To deal with an increasingly competitive environment, organizations are combining continuous improvement (CI) practices with digitalization to accrue their benefits on operational performance and achieve operational excellence. The purpose of this study was to identify the enablers and inhibitors of digitalization as part of CI projects. Design/methodology/approach A mixed-methods sequential explanatory research design consisting of an online survey and semi-structured interviews was used to examine how digitalization technologies have been incorporated by organizations in their CI projects. Findings Key enablers of digitalization were found to be leadership capabilities, strategic direction, stakeholder involvement, system compatibility, data quality and giving employees room to experiment. Knowledge of digitalization was found to affect all these enablers. Research limitations/implications The empirical findings are based on a nonprobability sample of Dutch CI practitioners, limiting their generalizability. Practical implications The empirical findings highlight the need for organizations to adopt a structured approach to implementing digitalization as part of their CI projects, starting by ensuring that the necessary knowledge and skills are either present or accessible to the organization. Originality/value The empirical findings show that enablers of digitalization in the context of CI are strongly interlinked, and thus require a holistic approach.

Rathi R., Singh M., Antony J., Garza-Reyes J.A., Goyat R., Shokri A.

Purpose This study aims to explore the potential application of blockchain technology in Lean Six Sigma (LSS) project through a proposed blockchain-LSS (BLSS) model. The proposed model can tackle real-time problems in information sharing, transparency and traceability in every stage of the LSS project. Design/methodology/approach The scoping review approach is used to develop the integrated model of the BLSS approach for operational excellence. The proposed model is validated through expert’s input, which is collected by a questionnaire survey method. Findings The prime function of the proposed BLSS model is the information sharing among the project team and real-time monitoring, transparency, traceability and immutability in the Define-Measure-Analyze-Improve-Control phase. The proposed model also consists the information about the role of blockchain features at each phase of the LSS project. The project team and industry employees can trace the success of the project at every moment, resulting in trust buildup and the elimination of fake data. Moreover, there would be no disputes among various sections/shops of the plant and employees to share the real information. Practical implications This paper provides guidelines to practitioners and managers for integrating the LSS approach and blockchain. The blockchain helps managers and practitioners in better data traceability and transparency, monitoring of data as well as more sustainable LSS project management. Originality/value To the best of the authors’ knowledge, this is the first research attempt that developed an integrated model of blockchain and LSS approach to maintaining the immutable records of assets in projects and targeted Industry 4.0.