José Faria

An analytical methodology for the dependability evaluation of non-Markovian systems with multiple components

Abstract Very often, in dependability evaluation, the systems under study are assumed to have a Markovian behavior. This assumption highly simplifies the calculations, but introduces significant errors when the systems contain deterministic or quasi-deterministic processes, as it often happens with industrial systems. Existing methodologies for non-Markovian systems, such as device stage method [1] , the supplementary variables method or the imbedded Markov chain method [2] do not provide an effective solution to deal with this class of systems, since their usage is restricted to relatively simple and small systems. This paper presents an analytical methodology for the dependability evaluation of non-Markovian discrete state systems, containing both stochastic and deterministic processes, along with an associated systematic resolution procedure suitable for numerical processing. The methodology was initially developed in the context of a research work [3] addressing the dependability modeling, analysis and evaluation of large industrial information systems. This paper, extends the application domain to the evaluation of reliability oriented indexes and to the assessment of multiple components systems. Examples will be provided throughout the paper, in order to illustrate the fundamental concepts of the methodology, and to demonstrate its practical usefulness.

An Agile BPM System for Knowledge-Based Service Organizations

This paper presents a business process management (BPM) system aimed at knowledge-based service organizations. The core activity of these organizations consists on the delivery of high-valued services tailored to each customer. When compared to product-based organizations, service organizations have more dynamic and diversified business portfolios and business processes, due to the need to adapt to evolving customer needs. The efficiency of business process management (BPM) solutions is widely recognised as far as high volume standardized processes are concerned, but the unsuitability of these systems to handle customizable service requests is also widely acknowledged. With this in mind, a new BPM platform, hereafter referred to as the soBPM platform, was designed and deployed. This platform is intended to offer a higher degree of flexibility, both at process design-time and process run-time. The platform implements a soft-automation process management approach that will be discussed in the first part of the paper. Then, the deployment of the platform at the Shared Service Center of a large University will be presented.

Cost and quality of service analysis of production systems based on the cumulative downtime

The paper presents a method for the analysis and design of industrial production systems based on a joint assessment of the cost and the quality of service. The operation of a production system is seen as the accomplishment of a sequence of missions, each one corresponding to the cost-effective production and delivery of a specified quantity of products within a specified time frame. The paper shows that the probability of successfully accomplishing a mission is a non-linear function of the cumulative production downtime and that this time cannot be obtained using conventional Markov based techniques. The paper also introduces an analytical model and a procedure that allows the density function of the downtime to be obtained and shows how, using these tools, the production costs and the quality of service may be assessed and related to the internal design of the shop floor. The method seems to be particularly valuable in the analysis of production systems integrated in just-in-time supply chains, in which the reliability of the deliveries is an outstanding requirement.

Product lifecycle management in knowledge intensive collaborative environments: An application to automotive industry

Today, manufacturing is moving towards customer-driven and knowledge-based proactive production. Shorter product life cycles lead to increased complexity in areas such as product and process design, factory deployment and production operations. To handle this complexity, new knowledge-based methods and technologies are needed to model, simulate, optimize and monitor manufacturing systems. Product lifecycle management research tends to focus on situations that are responsive to formal analysis and modelling. However, in several domains such as knowledge intensive collaborative environments, its not possible to model processes using formal notations. Knowledge based and collaborative process management involves a combination of structured and non-structured processes. Structured processes management can be reduced to a set of fully-defined rules leading to high efficiency but also low flexibility, whereas the management of non-structured processes is not prone to a full formalization. A combination of both structured and unstructured management approaches is required in order to achieve a successful trade-off between efficiency, flexibility and controllability. We call a process as semi-structured when it contains both structured and non-structured sub-processes leading to a flexible and efficient hybrid approach. Large enterprise information systems, impose structured and predictable workflows, while knowledge based collaborative processes are unpredictable to some extent, involving high amount of human-decision. Moreover, large enterprise information systems are not able to manage the daily ad hoc communication inherent to the knowledge-based process itself. This paper introduces a set of concepts, methods and tools of an innovative Hybrid Process Management approach validated by a real world business case in the automotive industry.

Business Process Monitoring and Management in Virtual Enterprise Through Interactive User Interface Layer

This research provides mechanisms that facilitate to monitor and manage of Virtual Enterprise (VE) collaborative business processes in an efficient and effective way. First, it shows a self-contained process monitoring tool specification that contains the following main functionalities: events capturing from a workflow engine, business activity monitoring, process analytics and monitoring rules definition and evaluation. An interactive user interface layer in the form of dashboard is then highlighted within the scope of this research with the objective to monitor the VE operational processes. The dashboard will be the integration platform for a set of components that allow the establishment and operation of VE successfully. This platform enables a seamless integration of business processes and provides an end-to-end ICT solution among the VE member organizations. The work presented in this paper is developed within the scope of the European Commission NMP priority of the Seventh RTD Framework Programme for the ADVENTURE (ADaptive Virtual ENterprise ManufacTURing Environment) project.

Supporting the Operation of Semi-structured Work Systems

A semi-structured work system (SSWS) combines business processes and activities with different specification levels, from highly structured workflow processes to loosely structured collaborative activities. In the first part of the paper, the fundamental concepts regarding business process management systems are reviewed in order to highlight their shortcomings as far as the management of SSWS is concerned. The second part of the paper discusses the requirements of information systems targeted to support effectively the activity of SSWS. The final part of the paper introduces a system that was developed accordingly to those requirements and the preliminary results of their application.

Building an Extended Ontological Perspective on Service Science

This paper presents an approach accounting for the classification of the main knowledge resources related to the new Science of Service. The main knowledge categories are defined as concepts integrated in an extended Service Science ontology. The ontology derived from several sources was captured using UML and Protege, and then, through a RDF/OWL transformation, a semantically annotated wiki has been directly implemented offering an execution of the ontology together with implemented use cases. Further, a dedicated application was developed – the Service Science Knowledge Environment (SSKE) – in order to grant user access to different knowledge categories created along with the proposed ontology. The SSKE is a cloud based collaborative software service, aiming at providing co-created knowledge resources shared by academia, industry and government organizations. This application can be accessed through the Web ( http://sske.cloud.upb.ro/ ) and it can be used for managing service related knowledge.

On the Reliability Evaluation of Failure Delayed Industrial Systems

This paper presents an analytical approach for the evaluation of multi-user safety critical systems presenting a failure delayed behavior pattern. As a consequence of a failure event, the performance of these systems worsens progressively due to the internal fault tolerance mechanisms or the complacency of the users regarding the temporary unavailability of the services. A distinctive feature of the approach is the ability to handle stochastic models containing multiple processes with generalized distributions. The approach is based on the determination of analytical expressions to measure reliability, for instance, frequency and probability of failure states, which may be evaluated using general purpose mathematical tools. The paper first reviews other well-established techniques employed in the assessment of non-Markovian systems, particularly those based on stochastic Petri nets. The rationale of the new approach and its fundamental algorithms are presented together with a set of illustrative examples which highlight the strengths of the approach, as well as its limitations. Copyright

RELIABILITY ENGINEERING OF LARGE JIT PRODUCTION SYSTEMS

This paper introduces the rationale and the fundamental elements and algorithms of a reliability engineering methodology combining analytical and simulation tools, and discusses its application to the design of a large, multi-cell and heterogeneous production system with just-in-time (JIT) deliveries. In order to cope with the inherent complexity of such analysis, a two level hierarchical modeling and evaluation framework was developed. Local models are first obtained from the failure and repair processes of the manufacturing equipment. Then, these models are combined with the failure propagation delays introduced by the work-in-process buffers in order to obtain the system level model. The evaluation algorithm is able to deal with reliability models containing stochastic processes with generalized distributions. This fundamental requirement comes from the fact that repair and failure propagation processes typically present hyper-exponential distributions, e.g., lognormal distributions, that cannot be assessed using the conventional reliability techniques. The second part of the paper addresses several design issues of the production system that directly impact the reliability of the deliveries, and explains how the behavioral and structural characteristics of JIT production systems were explored in order to implement effective evaluation algorithms.

Large Project Management in the Automotive Industry: A Flexible and Knowledge Based Approach

This paper presents a novel approach on flexible and knowledge intensive process management, driven by a large automotive industry case study. The automotive company in analysis requires a very dynamic behaviour, based on high flexibility of both people and equipment. Market has been imposing a decreasing of automotive products life cycles, increasing the number of line adaptations during the entire value chain, resulting in an increased complexity from product design to production. To handle this complexity, new knowledge-based methods and technologies to model, simulate, optimize and monitor planned and existing manufacturing systems are required. Existing large Enterprise Information Systems impose totally structured and predictable workflow, while knowledge intensive processes are flexible and unpredictable, involving high amount of human-decision and interaction. This lead to the need of development of highly specialized applications. This paper presents a novel hybrid approach, including work, information and communication management, to support knowledge intensive processes. The application of the new solution in the automotive engineering process management proved to be very effective and efficient, leading to significant savings.