One of the significant challenges for current and future manufacturing systems is that of providing rapid reconfigurability in order to evolve and adapt to mass customization. This challenge is aggravated if new types of processes and components are introduced, as existing components are expected to interact with the novel entities but have no previous knowledge on how to collaborate. This statement not only applies to innovative processes and devices, but is also due to the impossibility to incorporate knowledge in a single device about all types of available system components. This paper proposes the use of Semantic Web Services in order to overcome this challenge. The use of ontologies and explicit semantics enable performing logical reasoning to infer sufficient knowledge on the classification of processes that machines offer, and on how to execute and compose those processes to carry out manufacturing orchestration autonomously. A series of motivating utilization scenarios are illustrated, and a research roadmap is presented.Index Terms-Knowledge based systems, manufacturing automation, reconfigurable manufacturing systems, Semantic Web Services.

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The enterprises to be competitive are constantly looking for continuous increase of productivity, quality and level of services. With the development of Industry 4.0 concept, manufacturers are more confident about new advantages of automation and systems integration. Lean management is well developed and empirically proven effective managerial approach. Combining Lean and Industry 4.0 practices seems to be necessary evolutionary step for further raise the level of operational excellence (exploitation of finance, workload, materials, machines/ devices). There is an increasing number of Industry 4.0 solutions used to reduce waste (as known from Lean Management). Therefore, the main objective of this article aims at presenting the results of a literature review on the concept of 'Lean Industry 4.0ʹ. Dynamic methodology called "Systematic Literature Network Analysis (SLNA)" was used. It combines the Systematic Literature Review approach with the quantitative analysis of bibliographic networks to detect emerging topics and the dynamic evolution of the topics. The paper is a comprehensive systematization and rationalization of knowledge about the integration of LM and I4.0 concepts, identifies the most important research trends and defines directions for future research. The article contains a framework that presents the current state of knowledge in the area of Lean Industry 4.0.

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