The exponential growth of cutting-edge technologies continuously pushing the manufacturing industry into the paradigm of smart manufacturing. Smart manufacturing provides the pace of highly competitive market demand and customized intensive production. The goal of smart manufacturing technologies embedded systems in the Industry 4.0 paradigm and lean production is to enhance the flexibility in all tears of the enterprise. It is a big challenge, to measure the flexibility of smart systems for decision-making and adaptation of the new manufacturing technologies. The conceptual architecture of smart manufacturing systems has been proposed to solve the problem. Operational flexibility has been measured using a mathematical model for smart manufacturing in the Open Platform Communication Unified Architecture enabled Cyber-Physical Production System at shop floor level and validated. The results obtained from experimentation depict the operational flexibility, maximum capacity, and breakeven point of the manufacturing system have been improved by using smart manufacturing technologies. The proposed model improves the product manufacturing using Smart Computer Numeric Control Machining, Smart Autonomous Robotic Machining, Smart Additive Manufacturing and Smart Hybrid Additive & Subtractive Manufacturing up to 30.4%, 53.6%, 55% and 65% respectively. It will also help the decision-makers to overcome the challenges of transformation from conventional to smart manufacturing industry 4.0 paradigm.

Developing countries are facing challenges to adopt the Industry 4.0 in their manufacturing sector. One of the reasons is lacking technological and maturity models’ compatibility to assess the current state of maturity and readiness level. This empirical research has presented a maturity model based on the IMPULS models developed by the German Association of Mechanical Engineers and the Singapore Smart Industry Readiness Index with some modifications. A comprehensive and compatible lean modified manufacturing maturity model for Industry 4.0 (LM4I4.0) has been developed and validated. The proposed model has add-on dimension of the lean philosophy. This modification provides the facility to integrate the two main manufacturing paradigms of lean and Industry 4.0. The developed LM4I4.0 has been validated in fifty manufacturing industries of Pakistan and results have been presented in the data analysis format. The data mining, dimension cluster analysis, and computation of data shows that the proposed model is compatible for the developing country. Moreover, the results and analysis show that the maturity level of Pakistani manufacturing is 3.39, which means companies are immature in context of Industry 4.0. The proposed methodology may be used to conduct self-evaluations and enable businesses to undertake self-assessments in order to align themselves with Industry 4.0 in a systematic way. It will, therefore, provide a direction to formulate the enterprise transformation strategies in Industry 4.0 paradigm.

Development of design characteristics based dynamic decision support framework is presented in the current study, to facilitate the decision makers in the transformation of system in the industry 4.0 paradigm. The model development is designed for a robust decision-making approach to integrating...

The primary objective of this study is to evaluate the adaptability and inclination of industrial sectors of Pakistan with respect to Industry 4.0. A questionnaire with nine questions was developed and disseminated to 20 sampled industries. To analyze the variability in responses, a one-way analysis of variance test was used. The statistical analysis revealed that there is an awareness of the basic concept behind Industry 4.0 in Pakistani industries, but there is a reluctance to adopt digitization and to shift from conventional production systems. This study will be helpful and will provide a guide for new and already existing enterprises for achieving Industry 4.0 requisite attributes precisely.