Conceptualised Visualisation of Extended Agent Oriented Smart Factory (xAOSF) Framework with Associated AOSR-WMS System

Abstract

The emergence of the fourth industrial revolution (Industry 4.0) has sparked proliferation in thedomain of Cyber-Physical Systems (CPS), and extensive research has been conductedin this area since its beginning. However, recent literature claims that Smallto Medium Size Enterprises (SMEs) are not getting the benefits of Industry 4.0 (I4.0) in a full potential because of unresolved compatibility-mismatch issues and involvement of high infrastructuralcost. In order to help bridge this gap, the Extended Agent-Oriented Smart Factory (xAOSF) framework provides a high-level guideline solution, integrating the whole supply chain (SC), from supplier-end to customer-end with an objective to expose SMEs towards the benefits of I4.0. This paper, as part of a publication series, provides a conceptualised visualisation of the xAOSF framework as a customised CPS,which presents an elegant mediation mechanism between multiple xAOSF agents to uptake negotiation and coordination schemes at different enterprise levels. This paper also includes detail on howthe I4.0 based xAOSF framework caters to three-dimensional enterprise integration, in order to provide seamless connectivity and robustness in enterprise-wide operations. Furthermore, for the purpose of validation and to justify the claim, the experimentation is performed by applying a comprehensive test scenario onxAOSF's recommended AOSR WMS strategy in comparison with linear SC-based standard WMS system, which yields a substantial performance improvement in certain key-performance areas.

Using Artificial Intelligence (AI) to predict organizational agility

“…The most effective AI methodologies are Machine Learning (ML) methods e.g., Support Vector Machine (SVM), Decision Trees (DT), and K-Nearest Neighbours (KNN), as detailed in the later sections, which have been utilised in this research article to predict organizational agility. Applications of AI and ML methods include commercial use of SVM [ 16 – 19 ], energy load management [ 20 ], finance and portfolio management, inventory management [ 21 , 22 ], sales forecasting, profit maximisation, and sales growth [ 23 ], among other domains e.g., dynamic cognitive networking approach [ 18 ], modelling and identifying frailty [ 24 , 25 ]. In order to maximise the potential of revenue generation, predicting Organizational Agility (OA) is an important factor.…”