Technological developments along with the emergence of Industry 4.0 allow for new approaches to solve industrial problems, such as the Job-shop Scheduling Problem (JSP). In this sense, embedding Multi-Agent Systems (MAS) into Cyber-Physical Systems (CPS) is a highly promising approach to handle complex and dynamic JSPs. This paper proposes a data exchange framework in order to deal with the JSP considering the state-of-the-art technology regarding MAS, CPS and industrial standards. The proposed framework has self-configuring features to deal with disturbances in the production line. This is possible through the development of an intelligent system based on the use of agents and the Internet of Things (IoT) to achieve real-time data exchange and decision making in the job-shop. The performance of the proposed framework is tested in a simulation study based on a real industrial case. The results substantiate gains in flexibility, scalability and efficiency through the data exchange between factory layers. Finally, the paper presents insights regarding industrial applications in the Industry 4.0 era in general and in particular with regard to the framework implementation in the analyzed industrial case.

Purpose: Business process management (BPM) and lean management (LM) are both recognized for improving organizational performance through continuous improvement, yet their similarities and differences have been poorly discussed so far. This paper aims to find their main differences and similarities using a systematic method for literature review.Design/methodology/approach: The paper uses a structured literature review known as SYSMAP (Scientometric and sYStematic yielding MApping Process). The method integrates bibliometrics and content analysis procedures to perform in-depth analysis of the literature at hand.Findings: Both methodologies seek continuous improvement with focus on the customer and process standardization, but they are divergent mainly in relation to the flow they intend to improve. The impossibility of implementing both methodologies in an effective way was also observed, mainly due to the differences they present in relation to how to achieve the continuous improvement cycle.Research limitations/implications: As any other literature reviews, the major limitation is to have omitted relevant literature even though all available procedures have been used to avoid this situation.Practical implications: This paper offers a novel perspective from the practitioner side. LM may be better used in human-intensive process improvement whereas BPM in technology-intensive ones. Such characteristics open up new opportunities for practitioners aiming at integrating both approaches.Originality/value: This is the first paper that systematically analyses the body of literature of BPM and LM with the means to better understand their similarities and differences.