Implementation Strategies for Industry 4.0 Enabling Technologies in Indian Manufacturing Industries

Abstract

In recent years, competition among the Indian Manufacturing Industries (IMIs) has increased enormously in the global market. The current uncertainty in the market context is characterised and governed by the customised requirements of the customers. Thus, the manufacturing system in the industries should be capable of adapting the parameters like flexibility in scalability, variety, agility, system responsiveness, inter-connectivity, automatic data exchange with communication among the manufacturing systems, transparency and human-machine interaction, which are the main components and principles of Industry 4.0 (I4.0). Thus, adopting I4.0 is vital in corroborating its long-term survival in the global marketplace. However, very few research work considerations contribute to the issues induced by adopting I4.0 in manufacturing industries. Initially, 13 Industrial System Requirements (ISRs) of IMIs along with 18 barriers faced by these industries during implementing I4.0 enabling technologies in existing systems were identified through literature review and industry experts’ feedback. This work aims to minimise the gap between the existing ISRs, and the challenges faced during implementing I4.0 technologies in existing Industries. The identified ISRs and barriers were evaluated and analysed based on the data set collected from a questionnaire-based survey. Fuzzy multi-criteria analysis is conducted to identify the most weighted ISRs and barriers, and ranked them concerning their importance. The most dominant ISR is found to be ‘Transparency through real-time data monitoring and exchange’ while the most dominant implementing barrier obtained is ‘Employee inflexibility to learn and adapt’. This work offers the researchers, practitioners and industrialists an opportunity to formulate and solve multi-criteria decision-making problems through numerous case studies to prioritise the ISRs and barriers for analysis. Next, the inter-item correlation between the ISRs and barriers were investigated. These correlation values produced from the analysis show how the implementation barriers affect each system’s needs. The collected values of the degree of correlation between each ISR and each barrier have been used to narrow down the gap between existing ISRs and barriers. The maximum positive degree of correlation is found between ISR ‘Increasing system responsiveness’ and the barrier ‘Lack of quick reconfiguration of systems’. It guides industrial specialists, decision-makers, solution providers and researchers in narrowing down the search space to focus on the highest degree of correlated factors. These correlations can create multiple frameworks, conceptual models, maturity models, readiness models and strategical approaches for Indian firms to efficiently implement I4.0 technology. Based on these findings along with a team of eight experts taken from an Indian industry, a Conceptual Framework-based Architecture (CFA) was designed, developed and validated in three phases as per their existing production environment, current technologies, ISRs and barriers faced during the process of upgradation. The proposed CFA allows industrial strategists, decision-makers, policymakers, and researchers to use it as an architectural reference tool for integrating I4.0 enabling technologies, and configuring them as per diverse theoretical, practical, managerial and social implications in the Indian manufacturing sector. In the next phase of the work, subsequent visit to the same Indian industry was conducted. This enabled to identifying significant 52 CFA elements that are currently required to implement in the existing industry with the help of a systematic literature review. These IEF elements were validated as per the readiness level to adopt them in considered industry with the help of a series of brainstorming sessions and interviews with industry experts. Consequently, all identified CFA elements were sorted and merged with their input, resulting in a novel set of 35 CFA elements for this industry. These elements are categorised into six distinct groups based on their functionality for adopting strategy and efficient decision analysis. These 35 CFA elements were analysed based on extent of their readiness to be adopted in the existing industry with the help of industry experts. The degree of significance and readiness to adopt these elements in the existing industry as per the priorities were evaluated through fuzzy-AHP multi-criteria decision analysis. This prioritisation of the sub-categorised framework elements helps in initiating the strategies for implementation process in this manufacturing plant. The most significant CFA element is found to be ‘Decision Making and Management Skills’. For the long-term sustainable implementation of CFA elements, a customised sustainable framework of these elements was designed. The causal relations among these elements were investigated through the fuzzy-DEMATEL method. The diagraphs of the causal relations from each group of the sustainable framework were mapped and interpreted to determine the influencing factors as well as the factors that get influenced. ‘Central Database Server’ is determined to be the most significant sustainable framework element, while the maximum number of casual relationships is obtained from the categorised group, ‘Skill upgradation of the workforce’. This approach has a higher benefit in diverse sectors since it helps decision-makers to visualise and identify issues graphically, hence facilitating a better grasp of causal relationship, which are often complicated and hard to perceive in real-life industrial environment. This study allows industrial strategists, decision-makers, policymakers and researchers to use the approach, framework and findings as a reference tool for integrating I4.0 enabling technologies in existing IMIs and configuring them based on their individual requirements. It also proposes hypothesis of implementations and diverse theoretical, practical, managerial and social implications to address the growing demand of I4.0 technologies in the Indian manufacturing sector.