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 decisionmaking 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.
Development of design characteristics based dynamic decision support framework is presented in current study, to facilitate the decision makers in transformation of system in the industry 4.0 paradigm. The model development is designed for robust decision making approach to integrate the human and machine knowledge to adopt the smart technologies and system design. The system is based on prioritization of the industry 4.0 design principles and characteristics including flexibility, self-adaptability, slef-reconfigurability, context awareness, decision autonomy and real-time capabilities. It has been revealed from industrial field study, the companies facing difficulty to transform the system, and systematics approach needed to overcome the challenge. A decision support framework has been developed an integrated approach to embed the human and machine knowledge. The machine knowledge feed through connected databases and integrated systems and human inputs the desired information in the developed system. The computation performed in two modules in hybrid mathematical modeling approach; 1) operational flexibility module and 2) prioritization module. The developed system has been validated through industrial case study, the results depicts the operational flexibility, has been measured with improvement using smart manufacturing systems and transformation characteristics prioritized using the Analytical Hierarchical Process. The developed framework has capability to help the system development and estimate the factors involve in transformation. It will also help the decision makers to overcome the challenges of migration from conventional to sustainable smart manufacturing.
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