Intelligent systems in production engineering and maintenance -- ISPEM 2017 : proceedings of the first International Conference on Intelligent Systems in Production Engineering and Maintenance ISPEM 2017 / [electronic resource]
Edited by Anna Burduk; Dariusz Mazurkiewicz.
- Cham, Switzerland : Springer, 2018.
- 1 online resource.
- Advances in intelligent systems and computing 637 .
Includes author index.
Preface; Organization; Contents; Sesion Separator "Intelligent Systems in Maintenance"; A Concept of an IT Tool for Supporting Knowledge Transfer Among Facility Maintenance Employees as Pa ... ; Abstract; 1 Introduction; 2 General Outline of the Proposed Tool's Functionality; 3 Database Structure; 4 Summary; Acknowledgements; References; An Intelligent System Supporting a Forklifts Maintenance Process; Abstract; 1 Introduction; 2 A Case Study; 2.1 Structure of Forklifts Classification; 2.2 Analyses of the Frequency of Maintenance Activities; 2.3 Fuzzy Logic in Support of FoMT Determination. 2.4 Analysis, Results and Discussion3 Conclusions; References; An Intelligent System Supporting a Maintenance Process of Specialised Medical Equipment; Abstract; 1 Introduction; 2 Analysis of the Data Concerning Medical Equipment Failures; 3 Risk of Failures Assessment; 3.1 Fuzzy Interference Process; 3.2 Parameters for the Proposed FIS; 3.3 Analysis, Results and Discussion; 4 Conclusions; References; Enabling Round-Trip Engineering Between P & I Diagrams and Augmented Reality Work Instructions in Main ... ; Abstract; 1 Introduction; 2 Aims and Requirements; 3 Concept. 4 Prototype Implementation and Validation5 Conclusion; References; Incident Detection in Industrial Processes Utilizing Machine Learning Techniques; Abstract; 1 Introduction; 2 Classification Methods -- Machine Learning Algorithms; 2.1 Support Vector Machines (SVM); 2.1.1 Radial Basis Function (RBF) Kernel; 2.1.2 Polynomial Function (POLY) Kernel; 2.2 Naive-Bayes (NB); 2.3 Logistic Regression (LR); 2.4 Decision Trees (DT); 2.5 Random Forest (RF); 2.6 Adaptive Boosting (AdaBoost); 3 Evaluation Measures -- Boosting Algorithm; 4 Setup of the Fault Detection Analysis Method; 4.1 Data Pre-processing. 4.2 Labeling4.3 Monte Carlo Simulation -- Cross-Validation; 4.3.1 Support Vector Machines; 4.3.2 Decision Trees -- Random Forests; 4.3.3 Naive Bayes -- Logistic Regression; 4.3.4 Adaptive Boosting Algorithm; 4.4 Simulation Results; 5 Conclusions; Acknowledgement; References; Intelligent Systems of Forecasting the Failure of Machinery Park and Supporting Fulfilment of Orders ... ; Abstract; 1 Among the Source Development Factors Contributing to the Definition of the Currently Developing Co ... ; 2 Internet of Things and Cyber-Physical Systems in the Industrial Plants. 3 Algorithm of Prediction of Failure with the Use of CPPS and IIoT4 Example Application of an Algorithm; 5 Summary and Conclusions; References; SmartMaintenance -- The Concept of Supporting the Exploitation Decision-Making Process in the Selecte ... ; Abstract; 1 Introduction; 2 The Assumptions of the SmartMaintenance Concept; 3 Computer-Aided Under the SmartMaintenance Concept; 4 Computer-Aided Under the SmartMaintenance Concept -- Case Study; 4.1 The Multi-model of the Technical Network System; 4.2 The Taxonomic Model of the Assessment of the Exploitation Policy.
The volume presents a collection of 44 peer-reviewed articles from the First International Conference on Intelligent Systems in Production Engineering and Maintenance (ISPEM 2017). ISPEM 2017 was organized by the Faculty of Mechanical Engineering, Wrocław University of Science and Technology and was held in Wrocław (Poland) on 28-29 September 2017. The main topics of the conference included the possibility of using widely understood intelligent methods in production engineering. New solutions for innovative plants, research results and case studies taking into account advances in production and maintenance from the point of view of Industry 4.0 were presented and discussed--with special attention paid to applications of intelligent systems, methods and tools in production engineering, maintenance, logistics, quality management, information systems, and product development. The volume is divided into two parts: 1. Intelligent Systems in Production Engineering 2. Intelligent Systems in Maintenance This book is an excellent reference resource for scientists in the field of manufacturing engineering and for top managers in production enterprises.