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One of the achievements of the fourth industrial revolution is smart manufacturing, a manufacturing system based on Industry 4.0 technologies that will increase systems' reliability, efficiency and productivity. Despite the many benefits, some barriers obstruct the implementation of this manufacturing system. This study aims to analyze these barriers.

One of the measures that must be taken is to identify and try to remove these barriers, which involves identifying the stakeholders and components of technology associated with each barrier. As such, the primary purpose of this paper is to present a systematic literature review in the field of smart manufacturing with a focus on barriers to implementation related to the stakeholders and components of technology.

This research conducted a systematic literature review in Scopus and Web of Science databases and considered the studies published until 2021 were examined. The central question of this paper is answered based on this literature review, in which 133 related studies and 15 barriers were identified.

The significant gap observed in the literature review is that no research has been conducted to determine the stakeholders and components of technology related to the barriers, making it a potentially worthwhile subject for future research. In addition, the results of this study may help managers to implement smart manufacturing.

This study provides two main originalities. The former is helpful information for managers to make effective decisions when they face smart manufacturing barriers. The latter is related to identifying critical research gaps through systematic literature review.

This chapter is designed to provide an overview of the challenges facing Industry 4.0, focussing on the manufacturing sector, and highlighting the specifics of small to medium-sized enterprises. Recent technologies for data science, analysts, robotics, and other smart manufacturing trends are discussed, and the opportunities, difficulties, and limitations for breakthrough development are highlighted.

This chapter seeks to explain the manufacturing industries that have gone a lot of transformation in recent years. The changes were brought as a result of implementation of Industry 4.0 technologies. The aim of this chapter is to study Smart Manufacturing (SM) and to implement Industry 4.0 in a Sustainable Supply Chain. The study is qualitative which employs secondary sources of data. The data of the study were sourced from relevant published articles from 2017 to 23. Also the data were analyzed using thematic analysis. The results of the study revealed that, artificial intelligence (AI) Models, Cloud Connection, Smart Product, standard communication, cyber-physical system (CPS), virtual system builder among others are the requirements for adopting SM. While Augmented Reality (AR), 3D Printing, Big Data Analytics, AI, Internet of Things (IoT), among others are the major 14.0 technologies that enable Smart Manufacturing System (SMS). However, security issues, system integration, interoperability, multilingualism, standard interface, data quality, privacy concern, investment concern are the major challenges of implementing SMS for sustainable supply chain. This study concluded that, implementing SM in sustainable supply chain have significantly improved company's productivity, innovation, efficiency, effectiveness, cost-effective manufacturing operations as well as sustainable management.

The study explores the potential barriers to data science (DS) implementation in organizations and identifies the key barriers. The identified barriers were explored for their interconnectedness and characteristics. This study aims to help organizations formulate apt DS strategies by providing a close-to-reality DS implementation framework of barriers, in conjunction with extant literature and practitioners' viewpoints.

The authors synthesized 100 distinct barriers through systematic literature review (SLR) under the individual, organizational and governmental taxonomies. In discussions with 48 industry experts through semi-structured interviews, 14 key barriers were identified. The selected barriers were explored for their pair-wise relationships using interpretive structural modeling (ISM) and fuzzy Matriced’ Impacts Croise's Multiplication Appliquée a UN Classement (MICMAC) analyses in formulating the hierarchical framework.

The lack of awareness and data-related challenges are identified as the most prominent barriers, followed by non-alignment with organizational strategy, lack of competency with vendors and premature governmental arrangements, and classified as independent variables. The non-commitment of top-management team (TMT), significant investment costs, lack of swiftness in change management and a low tolerance for complexity and initial failures are recognized as the linkage variables. Employee reluctance, mid-level managerial resistance, a dearth of adequate skills and knowledge and working in silos depend on the rest of the identified barriers. The perceived threat to society is classified as the autonomous variable.

The study augments theoretical understanding from the literature with the practical viewpoints of industry experts in enhancing the knowledge of the DS ecosystem. The research offers organizations a generic framework to combat hindrances to DS initiatives strategically.

This study investigates the quantitative aspect of the various strains of operational excellence (OE) and competitive-potential (CP) in the SME sector. It has five steps, i.e., identifying the key performance constructs of OE and their hypothesized relationship pattern from literature, validating these constructs through factor analysis, formalizing their empirical relationships by structural-equation-modeling (SEM), path analysis of performance constructs with the empirical results, and lastly proposing a framework for OE deployment in SMEs.

Data for the deployment scores of operational excellence procedures (OEPs) were collected through a structured questionnaire survey. Nine hundred participants from a stratified random sample were approached for the survey, and 473 responses were received. Sample stratification was based on Gender, Education, Experience, Position, Department and Industry. Respondents had 5–30 years of experience managing manufacturing operations, holding the manager position and above.

The path analysis of the structural model provides unique insights into OE's practical aspects in SMEs (small and medium enterprises). For example, Contractual-conformance and Process-efficiency play pivotal roles as both have a significant positive impact on CP. Supplier efficacy, Consistency and Product-excellence do not improve CP unless mediated by Contractual-conformance or Process-efficiency.

The study provides important implications for academia, policymakers and managers. The study identifies and validates the operational excellence key performance practices and proposes a framework for manufacturing organizations. SME managers can follow the framework to develop effective operational excellence strategies to help them achieve their organizational goals. Additionally, the study emphasizes the need for continuous culture in SMEs, which will help to support operational excellence deployment. Overall, the implications presented in the study will help SMEs to enhance their competitiveness and operational performance.

The study explores the empirical investigation of the operational excellence deployment in SMEs. The study uses a mixed method approach for research design, including qualitative and quantitative approaches, and uses SEM to test the proposed framework. Validation of OE's six key performance constructs and establishing their empirical relation is an attempt to advance the Operations excellence theory. Unlike large enterprises, SMEs demonstrate an incohesive response to the practices pertaining to Supplier efficacy, Consistency and Product-excellence. This unique response pattern requires special treatment, which is incorporated into the proposed framework.

Purpose: In this chapter of this book, the role and contributions of blockchain in Industry 5.0 are examined. Especially, the advantages offered by blockchain in mass customization, hyper-personalization, human–robot collaboration and cognitive systems, which constitute the main theme of Industry 5.0, are mentioned.

Need for the study: With developing technology, revolutions are taking place in the industry. While these revolutions are occurring, various technologies serve as enablers. In this chapter, one of these technologies, blockchain, is examined.

Methodology: Industrial revolutions represent important technological developments for societies. In this chapter, Industry 5.0, one of these revolutions, is discussed. In the first section, the main themes of Industry 5.0 were examined. Afterward, the transition from Industry 4.0 to Industry 5.0 was analyzed. Then, the opportunities offered by Industry 5.0 were reviewed. Subsequently, the contributions of blockchain to Industry 5.0 were examined. Finally, the role of blockchain in Industry 5.0 is summarized.

Findings: The main themes of Industry 5.0 enable customized processes and smart production approaches. Blockchain makes significant contributions to these processes with its security and traceability features. In addition, smart contracts can increase transparency, traceability and security among stakeholders in the production process with their distributed ledger structure and immutability features. In blockchain networks, each transaction is carried out and approved by consensus. This consensus, provided by smart contracts, also secures transactions by reducing administrative costs. With these contributions, blockchain meets the security and smart management requirements of Industry 5.0.

The survival of companies today hinges on their adaptability and flexibility, with digital transformation (DT) and organizational slack (OS) playing crucial roles. Despite their recognized importance, these factors are often studied separately. This study aims to explore how OS facilitates DT and evaluate their synergies and trade-offs to improve performance.

Using data from the European Manufacturing Survey, structural equation modeling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA), we investigate causal relationships and possible combinations between different dimensions of OS and DT that contribute to business performance.

We confirmed the positive effect of OS and DT on business performance, highlighting the importance of organizational over technological factors. While not definitively establishing OS as a precursor to DT, our findings underscore the need for human and operational slack to improve performance, especially in less technology-intensive contexts.

Our findings evidence that decision-makers should integrate OS with DT initiatives to improve the firm’s competitiveness. However, it is worth noting that while OS seems essential in low-tech shopfloors, its importance is lower in high-tech environments. Furthermore, within the possible combinations, managers should promote operational slack and digitalization, as it seems fundamental to improve business performance.

This article contributes to the management field in three ways. First, it clarifies controversies by providing evidence of the positive roles of DT and OS as drivers of competitiveness for manufacturing firms. Second, we verify that OS is not directly linked to DT, challenging existing assumptions. Third, it investigates the combinations of OS and DT that drive business performance improvement, emphasizing their synergies and trade-offs.

This study aims to develop a production-oriented approach for optimal mass-customisation of floor panel layouts in cross-laminated timber (CLT) buildings. The study enables meeting building clients’ unique floor plan requirements at an optimal cost and simultaneously enhances manufacturers’ profit by minimising material and manufacturing process waste.

The present research uses a hybrid approach consisting of field data collection, mathematical modelling, development of a Genetic Algorithm (GA) and scenario analysis. Field data includes engineered timber production information, design data and building code requirements. The study adopts the Flexible Demand Assignment (FDA) technique to formulate a mathematical model for optimising the design of mass timber buildings and employs GA to identify optimal production solutions. Scenario analysis is performed to validate model outputs.

The proposed model successfully determines the load-bearing wall placement and building spans and specifications of floor panels that result in optimal production efficiency and the desired architectural layout. The results indicate that buildings made of a single category of thickness of panels but customised in various lengths to suit building layout are the most profitable scenario for CLT manufacturers and are a cost-effective option for clients.

The originality of the present study lies in its mathematical and model-driven approach towards implementing mass customisation in multi-storey buildings. The proposed model has been developed and validated based on a comprehensive set of real-world data and constraints.

The purpose of this paper is to analyze theory of inventive problem-solving (TRIZ) in terms of knowledge, skill, workload and affect to understand its effectiveness in enabling designers to achieve their optimized mental performance.

TASKS framework, which aims to capture the causal relations among Task workload, affect, skills, knowledge and mental stress, is adopted as our methodology. The framework supports the analysis of how a methodology influence designer’s affect, skills, knowledge and workload. TRIZ-related publications are assessed using the TASKS framework to identify the barriers and enablers in TRIZ-supported design.

TRIZ has limitations on its logic and tools. Nevertheless, it could create a beneficial impact on mental performance of designers.

This paper provides a theory-driven TRIZ usability analysis based on the materials in the literature following the TASKS framework. The impact of TRIZ, as an enabler or a barrier, has been analyzed in accomplishing a design task.

Company goals, behaviors and decision-making processes may differ depending on whether a given company decides to engage in the Industry 4.0 (I4.0) paradigm as a user or as a provider of I4.0-based solutions. This paper will consider this question in-depth by focusing on the extent to which the innovation ecosystem (IES) affects these two main strategies.

The authors' study aims to analyze the impact of a regional information and communication technology (ICT) ecosystem on the implementation of I4.0 at the company level by using an original survey of 123 companies that are already engaged in the implementation of I4.0 in the French region of Hauts-de-France and by employing two sets of logit models.

The authors' empirical study demonstrates the importance of an innovation ecosystem-based strategy for I4.0 technology provision. It reveals that engaging in R&D collaborative projects and developing links and complex relationships with heterogeneous actors within the IES positively affects the likelihood of a given firm deciding to implement I4.0 as a provider of I4.0-based solutions. This does not, however, affect the probability of a firm engaging in the I4.0 paradigm as a user of technologies and solutions.

From a policy standpoint, this study could encourage decision-makers to engage with I4.0 development by developing policies targeting the reinforcement of IES at a regional level. This could also help to accelerate the adoption of I4.0 technologies by manufacturing companies and foster the development of I4.0-based solutions through specific company-targeted policies. The authors' study supports the need for manufacturing company managers to evaluate and identify the best technological strategies related to the I4.0 paradigm that meet their specific needs.

The authors' study shows that the decision to engage in the I4.0 paradigm as providers of I4.0-based solutions is more likely to rely on an innovation ecosystem-based strategy, while the decision to engage in the I4.0 paradigm as users of I4.0-based solutions is more likely to rely on the company’s internal strategies, resources and demand-side benefits.