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Abstract
Integrated process planning and scheduling in networked manufacturing systems plays a crucial role nowadays and in the forthcoming context of Industry 4.0 to enable effective and efficient decisions, and to improve the business market, based on collaboration, along with computer-based distributed manufacturing and management functions. In this paper some insights regarding a literature review carried out about this main subjects analysed are presented and discussed. Moreover, a framework for integrated process planning and scheduling in networked manufacturing systems is proposed and briefly described, along with some main underlying issues, which are further discussed. Thus, the main purpose of this research consists on presenting a proposed methodology, based on the study conducted, to enable to further assist either academia or industry to develop new tools, techniques and approaches for integrated process planning in networked manufacturing environments. The findings and contributions of this research can help in the implementation and improvement in distributed manufacturing environments, to be linked with small and medium enterprises, to further expand their potentialities through well suited integrated process planning and scheduling decision making processes.
Highlights
In order to respond to today’s intensely competitive environment and to obtain high product variety and customization, along with short product life cycles, networked manufacturing environments, along with integrated production planning and scheduling systems play a crucial role to shift manufacturing and management paradigms from deterministic to a more rigorous, autonomous and dynamically adaptive control based on a flexible, agile and collaborative manufacturing
The findings and contributions of this research can help in the implementation and improvement in distributed manufacturing environments, to be linked with small and medium enterprises, to further expand their potentialities through well suited integrated process planning and scheduling decision making processes
The study and analysis of networked manufacturing has become a necessity due to its advantages in current competitive atmosphere, as it meets a number of, often conflicting, objectives and goals, such as reducing the manufacturing cycle time, shorter lead times, better interoperability, and maintaining the production flexibility leading to many feasible process plans, and all these requirements can be fulfilled through integrated process planning and scheduling (IPPS) based on appropriate supporting technologies for enabling integration, interoperability and digitalization, for reaching imperative main and common enterprise goals
Summary
In order to respond to today’s intensely competitive environment and to obtain high product variety and customization, along with short product life cycles, networked manufacturing environments, along with integrated production planning and scheduling systems play a crucial role to shift manufacturing and management paradigms from deterministic to a more rigorous, autonomous and dynamically adaptive control based on a flexible, agile and collaborative manufacturing. A befitting answer to this need is based on integrated production planning and scheduling through networked manufacturing (NM). The study and analysis of networked manufacturing has become a necessity due to its advantages in current competitive atmosphere, as it meets a number of, often conflicting, objectives and goals, such as reducing the manufacturing cycle time, shorter lead times, better interoperability, and maintaining the production flexibility leading to many feasible process plans, and all these requirements can be fulfilled through IPPS based on appropriate supporting technologies for enabling integration, interoperability and digitalization, for reaching imperative main and common enterprise goals. The main objective of this paper is to analyse, synthesise and present a comprehensive systematic literature review (SLR) of the role of integrated process planning and scheduling in networked manufacturing environments.
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