Mitigating the obsolescence of quality specifications models in service-based systems

Requirements-aware systems address the need to reason about uncertainty at runtime to support adaptation decisions, by representing quality of services (QoS) requirements for service-based systems (SBS) with precise values in run-time queryable model specification. However, current approaches do not support updating of the specification to reflect changes in the service market, like newly available services or improved QoS of existing ones. Thus, even if the specification models reflect design-time acceptable requirements they may become obsolete and miss opportunities for system improvement by self-adaptation. This articles proposes to distinguish "abstract" and "concrete" specification models: the former consists of linguistic variables (e.g. "fast") agreed upon at design time, and the latter consists of precise numeric values (e.g. "2ms") that are dynamically calculated at run-time, thus incorporating up-to-date QoS information. If and when freshly calculated concrete specifications are not satisfied anymore by the current service configuration, an adaptation is triggered. The approach was validated using four simulated SBS that use services from a previously published, real-world dataset; in all cases, the system was able to detect unsatisfied requirements at run-time and trigger suitable adaptations. Ongoing work focuses on policies to determine recalculation of specifications. This approach will allow engineers to build SBS that can be protected against market-caused obsolescence of their requirements specifications

Market-awareness in service-based systems

Service-based systems are applications built by composing pre-existing services. During design time and according to the specifications, a set of services is selected. Both, service providers and consumers exist in a service market that is constantly changing. Service providers continuously change their quality of services (QoS), and service consumers can update their specifications according to what the market is offering. Therefore, during runtime, the services are periodically and manually checked to verify if they still satisfy the specifications. Unfortunately, humans are overwhelmed with the degree of changes exhibited by the service market. Consequently, verification of the compliance specification and execution of the corresponding adaptations when deviations are detected cannot be carried out in a manual fashion. In this work, we propose a framework to enable online awareness of changes in the service market in both consumers and providers by representing them as active software agents. At runtime, consumer agents concretize QoS specifications according to the available market knowledge. Services agents are collectively aware of themselves and of the consumers' requests. Moreover, they can create and maintain virtual organizations to react actively to demands that come from the market. In this paper we show preliminary results that allow us to conclude that the creation and adaptation of service-based systems can be carried out by a self-organized service market system

Selection of obsolescence resolution strategy based on a multi criteria decision model

A component becomes obsolete when it is no longer available from its original manufacturer in its original form. Component obsolescence is a significant problem in the electronics industry. There are different strategies employed to address this problem, for example, using an alternative part, life time buy, redesign etc. Often, techniques used in industry select one of these options based on the most economical solution as determined by minimizing direct costs. However, there are factors other than cost, such as the number of suppliers, time constraints, reliability of the solution etc., which may play a crucial role in determining an overall best decision. In addition, there are multiple stakeholders like design, operations, manufacturing, sales, service etc., who might have different opinions when it comes to obsolescence management. This research provides a multi criteria decision model that will consider the trade-offs among multiple factors and provide the decision maker solution that will be acceptable to a wide variety of stakeholders as well as being viable from the company\u27s perspective. The model is based on multi attribute utility theory. It will provide the stakeholders a platform to express their preferences and experience in the decision process. And, based on the overall utility value, the most suitable obsolescence resolution strategy for a specific application will be provided. The research provides a hypothetical case study in order to illustrate the application and usage of the model

Systems Engineering Leading Indicators Guide, Version 2.0

The Systems Engineering Leading Indicators Guide editorial team is pleased to announce the release of Version 2.0. Version 2.0 supersedes Version 1.0, which was released in July 2007 and was the result of a project initiated by the Lean Advancement Initiative (LAI) at MIT in cooperation with: the International Council on Systems Engineering (INCOSE), Practical Software and Systems Measurement (PSM), and the Systems Engineering Advancement Research Initiative (SEAri) at MIT. A leading indicator is a measure for evaluating the effectiveness of how a specific project activity is likely to affect system performance objectives. A leading indicator may be an individual measure or a collection of measures and associated analysis that is predictive of future systems engineering performance. Systems engineering performance itself could be an indicator of future project execution and system performance. Leading indicators aid leadership in delivering value to customers and end users and help identify interventions and actions to avoid rework and wasted effort. Conventional measures provide status and historical information. Leading indicators use an approach that draws on trend information to allow for predictive analysis. By analyzing trends, predictions can be forecast on the outcomes of certain activities. Trends are analyzed for insight into both the entity being measured and potential impacts to other entities. This provides leaders with the data they need to make informed decisions and where necessary, take preventative or corrective action during the program in a proactive manner. Version 2.0 guide adds five new leading indicators to the previous 13 for a new total of 18 indicators. The guide addresses feedback from users of the previous version of the guide, as well as lessons learned from implementation and industry workshops. The document format has been improved for usability, and several new appendices provide application information and techniques for determining correlations of indicators. Tailoring of the guide for effective use is encouraged. Additional collaborating organizations involved in Version 2.0 include the Naval Air Systems Command (NAVAIR), US Department of Defense Systems Engineering Research Center (SERC), and National Defense Industrial Association (NDIA) Systems Engineering Division (SED). Many leading measurement and systems engineering experts from government, industry, and academia volunteered their time to work on this initiative

Supply Chain Planning with Incremental Development, Modular Design, and Evolutionary Updates

Proceedings Paper (for Acquisition Research Program)The policy specified by DoDI 5000.02 (DoD, 2008, December 8) prescribes an evolutionary acquisition strategy. Products with long lifecycles such as torpedoes, evolutionary updates via incremental development, modular design updates, technology refreshes, technology insertions, and Advanced Processor Builds are all in play at the same time. Various functional elements of the weapon system are often redesigned during the lifecycle to meet evolving requirements. Component obsolescence and failures must also be anticipated and addressed in upgrade planning. Within each weapon system''s evolutionary acquisition, cycle-changing requirements may expose weaknesses that have to be rectified across the inventory. New acquisition paradigms such as modular design have to be introduced into the supply chain while maintaining inventory levels of previously designed weapons at a high level of readiness. Thus, a diverse set of requirements must be satisfied with a finite set of resources. The acquisition policy does not provide guidance on how to address cross-coordination and optimization of project resources. This paper explores decision models for balancing conflicting demands and discusses the application of how these models address cross-coordination and optimization of project resources in the torpedo acquisition process while keeping the weapon''s efficiency and inventory effectiveness at or above minimum specified levels.Naval Postgraduate School Acquisition Research ProgramApproved for public release; distribution is unlimited

A MODEL FOR ESTIMATING THE COST TRADEOFFS ASSOCIATED WITH OPEN ELECTRONIC SYSTEMS

An open systems approach (OSA), especially when used in conjunction with modular architecture, reuse, and harnessing of existing (COTS or proprietary) technologies, is commonly associated with cost avoidances resulting from: more efficient design; increased competition among suppliers; more efficient innovation and technology insertion; and modularization of qualification. However, OSA strategies require investment and may increase risk exposure. To determine if openness should be pursued, and to what degree, a quantitative model assessing the costs associated with openness is required. Previous attempts to measure openness rely on qualitative measures, and cannot be used to estimate the life cycle cost impacts of openness. The model developed in this thesis quantitatively determines the effects of openness on life cycle cost. The life cycle cost difference between two implementations with differing levels of openness was calculated for a case study of an ARCI sonar system, providing insight into the value of openness. The case study performed in this thesis provides the first known quantitative support for Abts' COTS-LIMO hypothesis that increasing CFD increases cost avoidance. However, these results challenge Henderson's implicit assumption that marginal openness is always positive (increasing openness is always beneficial)

Early Warning System Potential for Single Sourcing Risk Mitigation

[EN] Network governance is described as a framework of policies and business rules, which is applied to manage an extended organization. Risk mitigation is crucial to avoid disruptions. A early warning systems could help to avoid these risk. In the paper a framework ro risk management using an early warning systems is presented.Franconetti Rodríguez, P.; Ortiz Bas, Á. (2014). Early Warning System Potential for Single Sourcing Risk Mitigation. IFIP Advances in Information and Communication Technology. 434:610-617. doi:10.1007/978-3-662-44745-1_60S610617434Enderwick, P.: Avoiding quality fade in Chinese global supply chains. Bus. Proc. Manag. J. 15(6), 876–894 (2009)Christopher, M., Lee, H.: Mitigating supply chain risk through improved confidence. Int. J. Phys. Dist. Log. Manag. 34, 388–396 (2004)Chopra, S., Sodhi, M.S.: Managing Risk to avoid Supply-Chain breakdown. MIT Sloan Manag. Rev., 53–61 (2004)Zeng, A.Z.: A synthetic study of sourcing strategies. Ind. Manage Data Syst. 100(5), 219–226 (2000)Wu, Z., Jiao, J., He, Z.: A single control chart for monitoring the frequency and magnitude of an event. Int. J. Prod. Econom. 119, 24–33 (2009)Macedo, P., Cardoso, T., Camarinha-Matos, L.M.: Value Systems Alignment in Product Servicing Networks. In: Camarinha-Matos, L.M., Scherer, R.J. (eds.) PRO-VE 2013. IFIP AICT, vol. 408, pp. 71–80. Springer, Heidelberg (2013)Tummala, R., Schoenherr, T.: Assessing and managing risks using the Supply Chain Risk Management Process (SCRMP). Suppl. Chain Manag. 16(6), 474–483 (2011)Franconetti, P., Ortiz, A.: Sourcing risk management in industrial collaborative networks. IEEE T. Ind. Inform. (under revision)Blackhurst, J.V., Scheibe, K.P., Johnson, D.J.: Supplier risk assessment and monitoring for the automotive industry. Int. J. Phys. Dist. Log. Manag. 38(2), 143–165 (2008)Scandizzo, S.: Risk Mapping and Key Risk Indicators in Operational Risk Management. Ec. Notes Banca Monte dei Paschi di Siena 34(2), 231–256 (2005)Stavrulaki, E., Davis, M.: Aligning products with supply chain processes and strategy. Int. J. Log. Manag. 21, 127–151 (2010)Chakraborty, D., Tah, D.: Real time statistical process advisor for effective quality control. Decision Support Systems 42(2), 700–711 (2006)Guiledge, T., Chavusholu, T.: Automating the construction of supply chain key performance indicators. Ind. Manag. Data Syst. 108(6), 750–777 (2008

Typology of Uncertainties in the Development Process of Product-Service Systems

This paper investigates uncertainty in the development of Product-Service Systems (PSS) – a complex combination of product and services. This research is important because practitioners struggle with managing the high uncertainties arising from the complexity of parallel product and service development in compound clusters of stakeholders. Yet, scholars have not analyzed these challenges extensively. Based on a combination of innovation management and servitization literature a conceptual framework is offered, detailing five uncertainty types relevant for PSS-development: environmental, technical, organizational, resource and relational uncertainty. This research contributes to the servitization literature by broadening the body of knowledge and deriving suitable management practices