Industry 4.0 and lean manufacturing practices for sustainable organisational performance in Indian manufacturing companies

The current literature claims the direct effects of industry 4.0 technologies (I4?T) on lean manufacturing practices (LMP) and sustainable organisational performance (SOP). LMP are also found to have a positive influence on SOP. However, the integrated effect of I4?T and LMP on SOP has not been empirically investigated. To address this gap, this research study investigates the indirect effects of I4?T on SOP with LMP as the mediating variable; furthermore, it aims to confirm or not the direct effects of I4?T on LMP and SOP. The study is based on data collected from 205 managers, working in 115 manufacturing firms. The findings suggest significant direct and indirect effects of I4?T on SOP and confirm the presence of LMP as a strong mediating variable. The results of the study extend the literature on I4?T by identifying I4?T as an enabler of LMP, leading to enhancement of the SOP. Implications and future research directions for academicians, practitioners, and consultants are provided.     

The link between Industry 4.0 and lean manufacturing: mapping current research and establishing a research agenda

In recent years, Industry 4.0 has emerged as one of the most discussed concepts and has gained significant popularity in both academia and the industrial sector. Both Industry 4.0 and lean manufacturing utilise decentralised control and aim to increase productivity and flexibility. However, there have been few studies investigating the link between these two domains. This article explores this novel area and maps the current literature. This is achieved through a systematic literature review methodology, investigating literature published up to and including August 2017. This article identifies four main research streams concerning the link between Industry 4.0 and lean manufacturing, and a research agenda for future studies is proposed.     

Impacts of Industry 4.0 technologies on Lean principles

Industry 4.0 is increasingly being promoted as the key to improving productivity, promoting economic growth and ensuring the sustainability of manufacturing companies. On the other hand, many companies have already partially or fully implemented principles and tools from the Lean management approach, which is also aimed at improving productivity. While the two approaches use very different strategies, they share some common principles. The objective of this article is to highlight the links between the principles and tools proposed by Industry 4.0 and those proposed by the Lean management approach, with a particular focus on how some of Industry 4.0's technologies are improving the implementation of Lean principles, depending on the technologies’ capability levels. As such, this study aims to provide a characterisation of the impacts of Industry 4.0 technologies on Lean principles according to targeted capability levels. The results obtained show strong support for Industry 4.0 technologies for Just-in-time and Jidoka, but little or no support for waste reduction and People and Team work. There is, therefore, a clear need to pursue the deployment of Lean management while improving certain Lean principles using Industry 4.0 technologies.     

Towards a lean automation interface for workstations

Methods and principles of Lean Production have become the major concepts to create highly efficient processes since the early 1990s. Due to its high effectiveness by reducing complexity and focusing on value-adding tasks, the Lean concept is still successful. Nevertheless, its changeability to produce highly customised products is limited. Industry 4.0 describes the vision of a smart production which can meet these future market requirements. Enablers are innovative information and communication technologies and the integration of all production entities into a common digital network. Lean Automation is the application of Industry 4.0 technologies to Lean Production methods in order to combine benefits from both domains. First proprietary Lean Automation solutions exist, but to enhance changeability in production, a common, unified communication interface is required. This paper presents the ongoing work towards an interface for digitising Lean Production methods using Cyber Physical Systems.     

Industry 4.0: Current practice and challenges in Malaysian manufacturing firms

This research employed a qualitative approach to discuss the current practice and challenges of Malaysian manufacturing firms in the implementation of Industry 4.0. The study examined data from seven manufacturing companies pursuing Industry 4.0 initiatives to identify various options for their strategies. The study found that the implementation of Industry 4.0 in the manufacturing firms is still in the exploratory stage. The companies involved in this study were discovered to conduct exploration using an adaptive-like framework. That is, throughout the process, the majority of the subjects are 'trying and adding' Industry 4.0 to their operations. Their trial-and-error approach is based on what is feasible and effective in their manufacturing environment. Overall, the investigation determined that data management and integration, as well as personnel re-education, were the respondents' primary operational challenges.     

Sustainable manufacturing in Industry 4.0: an emerging research agenda

This systematic review intends to identify how sustainable manufacturing research is contributing to the development of the Industry 4.0 agenda and for a broader understanding about the links between the Industry 4.0 and Sustainable Manufacturing by mapping and summarising existing research efforts, identifying research agendas, as well as gaps and opportunities for research development. A conceptual framework formed by the principles and technological pillars of Industry 4.0, sustainable manufacturing scope, opportunities previously identified, and sustainability dimensions, guided analysis of 35 papers from 2008–2018, selected by a systematic approach. Bibliometrics data and social network analysis complement results identifying how research is being organised and its respective research agendas, relevant publications, and status of the research lifecycle. Results point to that the current research is aligned with the goals defined by different national industrial programs. There are, however, research gaps and opportunities for field development, becoming more mature and having a significant contribution to fully developing the agenda of Industry 4.0.     

A framework for assessing the use of lean production practices in manufacturing cells

This study introduces a framework for assessing the use of lean production (LP) practices in manufacturing cells (MCs). The development of the framework included four stages: (a) defining LP practices applicable to MC, based on criteria such as the inclusion of practices that workers could observe, interact with and use on a daily basis; (b) defining attributes for each practice, emphasising the dimensions which were typical of their implementation in LP environments; (c) defining a set of evidence and sources of evidence for assessing the existence of each attribute–the sources of evidence included direct observations, analysis of documents, interviews and a feedback meeting to validate the assessment results with company representatives; (d) drawing up a model of the relationships among the LP practices, based on a survey with LP experts. This model supports the identification of improvement opportunities in MC performance based on the analysis of their interfaces. A case study of an MC from an automobile parts supplier is presented to illustrate the application of the framework.     

The industrial management of SMEs in the era of Industry 4.0

Industry 4.0 provides new paradigms for the industrial management of SMEs. Supported by a growing number of new technologies, this concept appears more flexible and less expensive than traditional enterprise information systems such as ERP and MES. However, SMEs find themselves ill-equipped to face these new possibilities regarding their production planning and control functions. This paper presents a literature review of existing applied research covering different Industry 4.0 issues with regard to SMEs. Papers are classified according to a new framework which allows identification of the targeted performance objectives, the required managerial capacities and the selected group of technologies for each selected case. Our results show that SMEs do not exploit all the resources for implementing Industry 4.0 and often limit themselves to the adoption of Cloud Computing and the Internet of Things. Likewise, SMEs seem to have adopted Industry 4.0 concepts only for monitoring industrial processes and there is still absence of real applications in the field of production planning. Finally, our literature review shows that reported Industry 4.0 projects in SMEs remained cost-driven initiatives and there in still no evidence of real business model transformation at this time.     

Industry 4.0 as an enabler of sustainability diffusion in supply chain: an analysis of influential strength of drivers in an emerging economy

Industry 4.0 (I4.0) and sustainability are recent buzzwords in manufacturing environments. However, the connection between these two concepts is less explored in the literature. In the current business context, the future generation of manufacturing systems is greatly influenced by the rapid advancement of information technology. Therefore, this study aims to examine the drivers of I4.0 to diffuse sustainability in Supply Chains (SCs). This research identifies the most relevant drivers through the literature and discusses them with area experts. Afterwards, an empirical analysis is conducted to validate the key drivers. Finally, the Grey based DEMATEL method is employed to examine the influential strength of the identified drivers and to build an interrelationship diagram. ‘Government supportive policies’ and ‘Collaboration and transparency among supply chain members’ were reported as highly significant drivers of I4.0. This study is an initial effort that investigates the key drivers of I4.0 to achieve high triple bottom line (ecological-economic-social) gains in SCs by taking an example from an emerging economy, i.e. India. This study may help managers, practitioners and policy makers interested in I4.0 applications to diffuse sustainability in SCs.     

A framework for operator – workstation interaction in Industry 4.0

We draw on cognitive and behavioural theories and on the artificial intelligence literature in order to propose a framework of future operator – workstation interaction in the ‘Industry 4.0’ era. We name the proposed framework ‘Operator – Workstation Interaction 4.0’. The latter’s capabilities permit an adaptive, ongoing interaction that aims to improve operator safety, performance, well-being, and satisfaction as well as the factory’s production measures. The framework is composed of three subsystems: (1) the observation subsystem which observes the operator and the processes occurring in the workstation, (2) the analysis subsystem which generates understanding and implications of the observations output, (3) the reaction subsystem which determines if and how to respond. The paper describes these elements and illustrate them using an example of a fatigued worker. The contributions, implications, and limitations of the proposed framework are discussed, and future research directions are presented.     

Remanufacturing in Industry 4.0

Using the theory of human blood circulation system, the authors explore the importance of remanufacturing in Industry 4.0. In this paper, they draw analogies between smart factory and human heart, between smart products and blood, and, between product function and nutrition and oxygen in the blood. Remanufacturing is analogous to the ingestion of oxygen and nutrition in lesser circulation or systemic circulation. Remanufacturing well supports recycling production, which is significant in realizing intelligent industry. Furthermore, this paper discusses the development direction of remanufacturing engineering in Industry 4.0 ages.     

Industry 4.0: Architecture and Equipment Revolution

The development of science and technology has led to the era of Industry 4.0. The core concept is the combination of “material and informationization”. In the supply chain and manufacturing process, the “material” of the physical entity world is realized by data, identity, intelligence, and information. Industry 4.0 is a disruptive transformation and upgrade of intelligent industrialization based on the Internet-of-Things and Big Data in traditional industrialization. The goal is “maximizing production efficiency, minimizing production costs, and maximizing the individual needs of human beings for products and services.” Achieving this goal will surely bring about a major leap in the history of the industry, which will lead to the “Fourth Industrial Revolution.” This paper presents a detailed discussion of industrial big data, strategic roles, architectures, characteristics, and four types of innovative business models that can generate profits for enterprises. The key revolutionary aspect of Industry 4.0 is explained, which is the equipment revolution. Six important attributes of equipment are explained under the Industry 4.0 perspective.     

Production management model integrating the principles of lean manufacturing and sustainability supported by the cultural transformation of a company

The search for superior production performance has been used by companies to overcome competition in the current global economic scenario. Efficient manufacturing connected to environmental initiatives provides a company with favourable conditions for maintaining uniform and continuous improvement in its competitive performance, while providing operational versatility to respond quickly to volatile markets. As production is one of the most expensive areas for a company, many organisations have sought a new management model for their production system that provides substantial productivity gains, cost saving opportunities and higher customer satisfaction. This study proposes a model of production management and an implementation method integrating the principles of lean manufacturing and sustainability, supported by cultural transformation at the company. Its objective was to achieve productivity gains and improvements on customer satisfaction, as well as develop the ability to provide quick responses to market changes in a globalised economy. The implementation of the proposed model should be gradual, initially addressing fundamental principles, and should operate simultaneously with, and in the same environment as, workforce development and organisational transformation initiatives, to create sustainable improvements.     

Cyber-based design for additive manufacturing using artificial neural networks for Industry 4.0

Additive Manufacturing (AM) requires integrated networking, embedded controls and cloud computing technologies to increase their efficiency and resource utilisation. However, currently there is no readily applicable system that can be used for cloud-based AM. The objective of this research is to develop a framework for designing a cyber additive manufacturing system that integrates an expert system with Internet of Things (IoT). An Artificial Neural Network (ANN) based expert system was implemented to classify input part designs based on CAD data and user inputs. Three ANN algorithms were trained on a knowledge base to identify optimal AM processes for different part designs. A two-stage model was used to enhance the prediction accuracy above 90% by increasing the number of input factors and datasets. A cyber interface was developed to query AM machine availability and resource capability using a Node-RED IoT device simulator. The dynamic AM machine identification system developed using an application programme interface (API) that integrates inputs from the smart algorithm and IoT interface for real-time predictions. This research establishes a foundation for the development of a cyber additive design for manufacturing system which can dynamically allocate digital designs to different AM techniques over the cyber network.     

Learning organisation and lean production: an empirical research on their relationship

This study aims at identifying the pairwise relationship between specific sets of Lean Production (LP) practices and Learning Organisation (LO) dimensions. More specifically, the association between 10 LP operational constructs and seven LO dimensions, based upon previous literature, is empirically examined. A survey-based study was carried out with 135 companies undergoing a LP implementation. The study sample was categorised according to two control variables: type of organisation and company’s LP implementation experience. Collected data was analysed through multivariate techniques. Results indicate that LP implementation and LO development are highly correlated. Additionally, findings also show that the extent of relationships varies according to the context, allowing the identification of synergistic associations and conflicting ones. The identification of these relationships provides means to better comprehend how the implementation of specific LP practices corroborates to enhancing LO capabilities within the organisation and vice-versa.     

Designing lean value streams in the fourth industrial revolution era: proposition of technology-integrated guidelines

Despite the envisioned interrelations, the way Industry 4.0 (I4.0) technologies can influence the design and implementation of lean value streams is still unknown and little empirical evidence is found in the literature. This article aims at proposing guidelines integrated with I4.0 technologies for designing lean value streams. We gathered experts’ opinions regarding the relationship between guidelines for designing a lean value stream and I4.0 technologies. The identification of the most important relationships provided arguments for the proposition of enhanced guidelines for designing lean value streams within the Fourth Industrial Revolution context. The integration of I4.0 technologies into the guidelines for designing a lean value stream raises a distinct approach that benefits from the simplicity and efficiency of Lean Production with ease and agility of the technologies typical of the Fourth Industrial Revolution. Such technology-integrated guidelines may allow overcoming existing barriers while lead companies to superior performance results.     

Intelligent Manufacturing in the Context of Industry 4.0: A Review

Our next generation of industry—Industry 4.0—holds the promise of increased flexibility in manufacturing, along with mass customization, better quality, and improved productivity. It thus enables companies to cope with the challenges of producing increasingly individualized products with a short lead-time to market and higher quality. Intelligent manufacturing plays an important role in Industry 4.0. Typical resources are converted into intelligent objects so that they are able to sense, act, and behave within a smart environment. In order to fully understand intelligent manufacturing in the context of Industry 4.0, this paper provides a comprehensive review of associated topics such as intelligent manufacturing, Internet of Things (IoT)-enabled manufacturing, and cloud manufacturing. Similarities and differences in these topics are highlighted based on our analysis. We also review key technologies such as the IoT, cyber-physical systems (CPSs), cloud computing, big data analytics (BDA), and information and communications technology (ICT) that are used to enable intelligent manufacturing. Next, we describe worldwide movements in intelligent manufacturing, including governmental strategic plans from different countries and strategic plans from major international companies in the European Union, United States, Japan, and China. Finally, we present current challenges and future research directions. The concepts discussed in this paper will spark new ideas in the effort to realize the much-anticipated Fourth Industrial Revolution.     

Industry 4.0: state of the art and future trends

Rapid advances in industrialisation and informatisation methods have spurred tremendous progress in developing the next generation of manufacturing technology. Today, we are on the cusp of the Fourth Industrial Revolution. In 2013, amongst one of 10 ‘Future Projects’ identified by the German government as part of its High-Tech Strategy 2020 Action Plan, the Industry 4.0 project is considered to be a major endeavour for Germany to establish itself as a leader of integrated industry. In 2014, China’s State Council unveiled their ten-year national plan, Made-in-China 2025, which was designed to transform China from the world’s workshop into a world manufacturing power. Made-in-China 2025 is an initiative to comprehensively upgrade China’s industry including the manufacturing sector. In Industry 4.0 and Made-in-China 2025, many applications require a combination of recently emerging new technologies, which is giving rise to the emergence of Industry 4.0. Such technologies originate from different disciplines including cyber-physical Systems, IoT, cloud computing, Industrial Integration, Enterprise Architecture, SOA, Business Process Management, Industrial Information Integration and others. At this present moment, the lack of powerful tools still poses a major obstacle for exploiting the full potential of Industry 4.0. In particular, formal methods and systems methods are crucial for realising Industry 4.0, which poses unique challenges. In this paper, we briefly survey the state of the art in the area of Industry 4.0 as it relates to industries.     

An empirical study for smart production for TFT-LCD to empower Industry 3.5

Abstract

With increasing technological advancements, manufacturing intelligence has become a crucial issue for maintaining competitive advantages. Industry 4.0, proposed by Germany, is one of the large-scale projects to achieve manufacturing intelligence and smart production. Others include the Advanced Manufacturing Partnership 2.0 (AMP2.0) from the United States, Industry 4.1J of Japan and Made in China 2025. On the other hand, most of the emerging countries may not be ready for the migration of Industry 4.0 directly since their industrial infrastructures are different with the leading countries. This study aims to propose Industry 3.5 as a hybrid strategy between existing Industry 3.0 and to-be Industry 4.0, in which digital decision-making, big data analytics, and manufacturing intelligence are integrated to empower smart production with disruptive innovations that can be realized in existing industrial infrastructure. To estimate the validity of the proposed Industry 3.5, an empirical study was conducted in a thin film transistor liquid crystal display (TFT-LCD) manufacturing factory in Taiwan. A smart daily planning and scheduling (DPS) system is developed to enhance manufacturing intelligence for smart production without a fully automation facility as the Cyber-Physical System proposed in Industry 4.0. This study concludes with discussions of development directions for industrial revolution.     

Production scheduling in the context of Industry 4.0: review and trends

Notwithstanding its disruptive potential, which has been the object of considerable debate, Industry4.0 (I4.0) operationalisation still needs significant study. Specifically, scheduling is a key process that should be explored from this perspective. The purpose of this study is to shed light on the issues regarding scheduling that need to be considered in the new I4.0 framework. To achieve this, a two-stage cascade literature review is performed. The review begins with an analysis regarding the opportunities and challenges brought by I4.0 to the scheduling field, outputting a set of critical scheduling areas (CSA) in which development is essential. The second-stage literature review is performed to understand which steps have been taken so far by previous research in the scheduling field to address those challenges. Thus, a first contribution of this work is to provide insight on the influence and expected changes brought by I4.0 to scheduling, while showcasing relevant research. Another contribution is to identify the most promising future lines of research in this field, in which relevant challenges such as holistic scheduling, or increased flexibility requirements are highlighted. Concurrently, CSA such as decentralised decision-making, and human–robot collaboration display large gaps between current practice and the required technological level of development.