MEBN-RM: A Mapping between Multi-Entity Bayesian Network and Relational Model

Multi-Entity Bayesian Network (MEBN) is a knowledge representation formalism combining Bayesian Networks (BN) with First-Order Logic (FOL). MEBN has sufficient expressive power for general-purpose knowledge representation and reasoning. Developing a MEBN model to support a given application is a challenge, requiring definition of entities, relationships, random variables, conditional dependence relationships, and probability distributions. When available, data can be invaluable both to improve performance and to streamline development. By far the most common format for available data is the relational database (RDB). Relational databases describe and organize data according to the Relational Model (RM). Developing a MEBN model from data stored in an RDB therefore requires mapping between the two formalisms. This paper presents MEBN-RM, a set of mapping rules between key elements of MEBN and RM. We identify links between the two languages (RM and MEBN) and define four levels of mapping from elements of RM to elements of MEBN. These definitions are implemented in the MEBN-RM algorithm, which converts a relational schema in RM to a partial MEBN model. Through this research, the software has been released as a MEBN-RM open-source software tool. The method is illustrated through two example use cases using MEBN-RM to develop MEBN models: a Critical Infrastructure Defense System and a Smart Manufacturing System

SERİ ÜRETİM HATLARINDA GÜVENİLİRLİK ANALİZİ İLE DURUMSAL FARKINDALIĞIN ARTIRILMASI

Bir işletmedeki üretim hatlarının performansı ve kapasitesi planlanmamış makine duruşları en aza indirilerek artırılabilir. Bu duruşların sıklıkla meydana geldiği üretim hatları için arızalar analiz edilmeli ve duruşlara neden olan sorunları azaltmak için bakım planlanması yapılmalıdır. Bu çalışmada, Minyatür Devre Kesici üretim hattında seri olarak çalışan makinelerin bakım planlaması için güvenilirlik analizine dayalı durumsal farkındalık modeli önerilmiştir. Durumsal farkındalık, üretim hattında plansız duruş hatalarını azaltmak için doğru kararların alınmasında ve planlamaların yapılmasında kullanılabilecek önemli bilgiler sağlayacaktır. Önerilen model, üretim hattında operatör, bakımcı ve yönetici düzeyinde durumsal farkındalığı artıracaktır. Güvenilirlik analiz için makinelerin duruş verileri Üretim Yönetim Sistemi üzerinden toplanmıştır. Güvenilirlik analizinde arızalanma süresi ve onarım süresi değerleri kullanılmıştır. Analiz yapılan zaman aralığındaki verilerden gelecekte darboğaz oluşturabilecek arızalar belirlenmiştir. Bakım planlamasında bu arızalara öncelik verilmelidir

Business analytics in industry 4.0: a systematic review

Recently, the term “Industry 4.0” has emerged to characterize several Information Technology and Communication (ICT) adoptions in production processes (e.g., Internet-of-Things, implementation of digital production support information technologies). Business Analytics is often used within the Industry 4.0, thus incorporating its data intelligence (e.g., statistical analysis, predictive modelling, optimization) expert system component. In this paper, we perform a Systematic Literature Review (SLR) on the usage of Business Analytics within the Industry 4.0 concept, covering a selection of 169 papers obtained from six major scientific publication sources from 2010 to March 2020. The selected papers were first classified in three major types, namely, Practical Application, Reviews and Framework Proposal. Then, we analysed with more detail the practical application studies which were further divided into three main categories of the Gartner analytical maturity model, Descriptive Analytics, Predictive Analytics and Prescriptive Analytics. In particular, we characterized the distinct analytics studies in terms of the industry application and data context used, impact (in terms of their Technology Readiness Level) and selected data modelling method. Our SLR analysis provides a mapping of how data-based Industry 4.0 expert systems are currently used, disclosing also research gaps and future research opportunities.The work of P. Cortez was supported by FCT - Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. We would like to thank to the three anonymous reviewers for their helpful suggestions

High tech automated bottling process for small to medium scale enterprises using PLC, scada and basic industry 4.0 concepts

The automation of industrial processes has been one of the greatest innovations in the industrial sector. It allows faster and accurate operations of production processes while producing more outputs than old manual production techniques. In the beverage industry, this innovation was also well embraced, especially to improve its bottling processes. However it has been proven that a continuous optimization of automation techniques using advanced and current trend of automation is the only way industrial companies will survive in a very competitive market. This becomes more challenging for small to medium scale enterprises (SMEs) which are not always keen in adopting new technologies by fear of overspending their little revenues. By doing so, SMEs are exposing themselves to limited growth and vulnerable lifecycle in this fast growing automation world. The main contribution of this study was to develop practical and affordable applications that will optimize the bottling process of a SME beverage plant by combining its existing production resources to basic principles of the current trend of automation, Industry 4.0 (I40). This research enabled the small beverage industry to achieve higher production rate, better delivery time and easy access of plant information through production forecast using linear regression, predictive maintenance using speed vibration sensor and decentralization of production monitoring via cloud applications. The existing plant Siemens S7-1200 programmable logic controller (PLC) and ZENON supervisory control and data acquisition (SCADA) system were used to program the optimized process with very few additional resources. This study also opened doors for automation in SMEs, in general, to use I40 in their production processes with available means and limited cost.School of ComputingM.Tech (Engineering, Electrical