Advanced Techniques for Assets Maintenance Management

16th IFAC Symposium on Information Control Problems in Manufacturing INCOM 2018 Bergamo, Italy, 11–13 June 2018. Edited by Marco Macchi, László Monostori, Roberto PintoThe aim of this paper is to remark the importance of new and advanced techniques supporting decision making in different business processes for maintenance and assets management, as well as the basic need of adopting a certain management framework with a clear processes map and the corresponding IT supporting systems. Framework processes and systems will be the key fundamental enablers for success and for continuous improvement. The suggested framework will help to define and improve business policies and work procedures for the assets operation and maintenance along their life cycle. The following sections present some achievements on this focus, proposing finally possible future lines for a research agenda within this field of assets management

The natural history of bugs: using formal methods to analyse software related failures in space missions

Space missions force engineers to make complex trade-offs between many different constraints including cost, mass, power, functionality and reliability. These constraints create a continual need to innovate. Many advances rely upon software, for instance to control and monitor the next generation ‘electron cyclotron resonance’ ion-drives for deep space missions.Programmers face numerous challenges. It is extremely difficult to conduct valid ground-based tests for the code used in space missions. Abstract models and simulations of satellites can be misleading. These issues are compounded by the use of ‘band-aid’ software to fix design mistakes and compromises in other aspects of space systems engineering. Programmers must often re-code missions in flight. This introduces considerable risks. It should, therefore, not be a surprise that so many space missions fail to achieve their objectives. The costs of failure are considerable. Small launch vehicles, such as the U.S. Pegasus system, cost around $18 million. Payloads range from$4 million up to $1 billion for security related satellites. These costs do not include consequent business losses. In 2005, Intelsat wrote off$73 million from the failure of a single uninsured satellite. It is clearly important that we learn as much as possible from those failures that do occur. The following pages examine the roles that formal methods might play in the analysis of software failures in space missions

Applying tropos to socio-technical system design and runtime configuration

Recent trends in Software Engineering have introduced the importance of reconsidering the traditional idea of software design as a socio-tecnical problem, where human agents are integral part of the system along with hardware and software components. Design and runtime support for Socio-Technical Systems (STSs) requires appropriate modeling techniques and non-traditional infrastructures. Agent-oriented software methodologies are natural solutions to the development of STSs, both humans and technical components are conceptualized and analyzed as part of the same system. In this paper, we illustrate a number of Tropos features that we believe fundamental to support the development and runtime reconfiguration of STSs. Particularly, we focus on two critical design issues: risk analysis and location variability. We show how they are integrated and used into a planning-based approach to support the designer in evaluating and choosing the best design alternative. Finally, we present a generic framework to develop self-reconfigurable STSs

Model-based dependability analysis : state-of-the-art, challenges and future outlook

Abstract: Over the past two decades, the study of model-based dependability analysis has gathered significant research interest. Different approaches have been developed to automate and address various limitations of classical dependability techniques to contend with the increasing complexity and challenges of modern safety-critical system. Two leading paradigms have emerged, one which constructs predictive system failure models from component failure models compositionally using the topology of the system. The other utilizes design models - typically state automata - to explore system behaviour through fault injection. This paper reviews a number of prominent techniques under these two paradigms, and provides an insight into their working mechanism, applicability, strengths and challenges, as well as recent developments within these fields. We also discuss the emerging trends on integrated approaches and advanced analysis capabilities. Lastly, we outline the future outlook for model-based dependability analysis

Framework for continuous improvement of production processes

This research introduces a new approach of using Six Sigma DMAIC (Define, Measure, Analyse, Improve, Control) methodology. This approach integrates various tools and methods into a single framework, which consists of five steps. In the Define step, problems and main Key Performance Indicators (KPIs) are identified. In the Measure step, the modified Failure Classifier (FC), i.e. DOE-NE-STD-1004-92 is applied, which enables to specify the types of failures for each operation during the production process. Also, Failure Mode and Effect Analysis (FMEA) is used to measure the weight of failures by calculating the Risk Priority Number (RPN) value. In order to indicate the quality level of process/product the Process/Product Sigma Performance Level (PSPL) is calculated based on the FMEA results. Using the RPN values from FMEA the variability of process by failures, operations and work centres are observed. In addition, costs of the components are calculated, which enable to measure the impact of failures on the final product cost. A new method of analysis is introduced, in which various charts created in the Measure step are compared. Analysis step facilitates the subsequent Improve and Control steps, where appropriate changes in the manufacturing process are implemented and sustained. The objective of the new framework is to perform continuous improvement of production processes in the way that enables engineers to discover the critical problems that have financial impact on the final product. This framework provides new ways of monitoring and eliminating failures for production processes continuous improvement, by focusing on the KPIs important for business success. In this paper, the background and the key concepts of Six Sigma are described and the proposed Six Sigma DMAIC framework is explained. The implementation of this framework is verified by computational experiment followed by conclusion section