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Journal articles on the topic 'Systems and processes engineering'

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Published: 10 December 2022
Last updated: 29 January 2023

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1

Buede, Dennis, Kevin Forsberg, Hal Mooz, Catherine Plowman, and Bob Tufts. "II. Systems Engineering Processes." INSIGHT 5, no. 1 (April 2002): 11–15. http://dx.doi.org/10.1002/inst.20025111.

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2

Wong, E., B. Hajek, and H. Saunders. "Stochastic Processes in Engineering Systems." Journal of Vibration and Acoustics 110, no. 3 (July 1, 1988): 421–22. http://dx.doi.org/10.1115/1.3269542.

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3

Sheard, Sarah, and Thomas H. Holzer. "2.4.3 Evolving Systems Engineering Processes: Moving from “What Systems Engineers Do” to “Engineering Systems“." INCOSE International Symposium 14, no. 1 (June 2004): 354–64. http://dx.doi.org/10.1002/j.2334-5837.2004.tb00501.x.

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4

Carpenter, Chris. "Guidance for Systems-Engineering Processes for Subsea Production Systems." Journal of Petroleum Technology 74, no. 08 (August 1, 2022): 61–63. http://dx.doi.org/10.2118/0822-0061-jpt.

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This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 31827, “Systems Engineering of Subsea Production Systems,” by Amedeo Marcotulli, Saipem, and David Wilkinson, Endeavor Management. The paper has not been peer reviewed. Copyright 2022 Offshore Technology Conference. Reproduced by permission. As the complexity and cost of subsea production systems (SPS) has increased during recent decades, the requirement for a more-rigorous, systematic approach toward the engineering of such systems has increased. A systems-engineering (SE) guidance document, specifically written to be applicable to SPS, is being developed by members of API Sub-Committee 17 at the time of writing. The objective of the complete paper is to make potential users of the guidance document aware of the benefits associated with the use of formal SE processes when designing complex facilities. SE Fundamentals Systems engineers exercise a high-level understanding of how system elements work together, visualizing complex systems as a set of subsystems that interact recursively. Recursive relationships are critical in SE and define many hierarchical taxonomies, such as the following: - System components consist of subsystems - Project activities consist of subprojects - Organizations consist of suborganizations - Contracts consist of subcontracts However, an elegance exists in the recursive nature of SE because its processes are self-similar and independent of scale. Its fractal nature allows application of the same process at any level and for any size of project, as shown in Fig. 1. The recursive and iterative nature of SE results in information flows in four directions: - Downward path: Requirement information flows from top to bottom, until the lowest elements are fully defined. - Upward path: Integration information flows from the lowest-level element. - Forward path: Interface information flows across elements that are at the same level, in each level. - Backward path: Feedback information informs the design and realization processes on every iteration for continuous improvement. SE formalizes the interfaces between disciplines, streamlining communications and avoiding rework. SE takes control of the iterations and recursions, thus minimizing waste. Therefore, SE reduces engineering cost while optimizing engineering design. SE requires a mindset more akin to an architect’s duties than to those of an engineer. It requires synthesis more than analysis, involving a top-down view of the system that goes further than an intimate analysis of its parts.
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5

Park, Chang-Su, and Keun-Taek Kim. "Systems Engineering Processes for KSLV-II Program." Journal of the Korea Society of Systems Engineering 10, no. 2 (December 30, 2014): 81–87. http://dx.doi.org/10.14248/jkosse.2014.10.2.081.

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6

Nazarevich, S. A., V. M. Balashov, and Yu V. Stovpets. "Information management model for systems engineering processes." Issues of radio electronics, no. 3 (April 26, 2020): 30–34. http://dx.doi.org/10.21778/2218-5453-2020-3-30-34.

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The goal of synchronized production is achieved through a proportional state of the mandatory components of the technology. Operational visualization of the activities of structural units and processes will allow us to move from stationary performance indicators to key performance indexes. Such transition is typical for enterprises accepting the TQM concept that includes orientation either on external or on internal customer. That is why the processes of operational activity should have not only vertical character for the whole hierarchic management structure for modern enterprise but also include reference points for controlling of continuous horizontal structures. As a result will be transition to the system of delayed and leading indicators that allows to create an ideological basis for the technological breakthrough to create of synchronized production.
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7

Daoutidis, Prodromos, W. Alex Marvin, Srinivas Rangarajan, and Ana I. Torres. "Engineering Biomass Conversion Processes: A Systems Perspective." AIChE Journal 59, no. 1 (December 6, 2012): 3–18. http://dx.doi.org/10.1002/aic.13978.

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8

Gilb, Tom. "Optimizing Systems Engineering Specification Quality Control Processes." INCOSE International Symposium 9, no. 1 (June 1999): 1221–26. http://dx.doi.org/10.1002/j.2334-5837.1999.tb00295.x.

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9

Cattan, Denise, and Ramón Lerchundi. "Improving Systems Engineering Processes Step by Step." INCOSE International Symposium 9, no. 1 (June 1999): 1477–81. http://dx.doi.org/10.1002/j.2334-5837.1999.tb00333.x.

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10

Gräßler, I., H. Thiele, B. Grewe, and M. Hieb. "Responsibility Assignment in Systems Engineering." Proceedings of the Design Society 2 (May 2022): 1875–84. http://dx.doi.org/10.1017/pds.2022.190.

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AbstractIncreasing system complexity can be controlled by using systems engineering processes. INCOSE defines processes with inputs and outputs (artifacts) for this purpose. Specific SE roles are used to organize the tasks of the processes within the company. In this work, the responsibilities for artifacts are evaluated by means of the RACI scheme and examined by a cluster analysis and discussed for a SE transformation project with a German automotive OEM. As a result of the study, the optimal composition for systems engineering teams is identified and the systems engineering roles are prioritized.
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11

Pavlov, S. Yu, N. N. Kulov, and R. M. Kerimov. "Improvement of chemical engineering processes using systems analysis." Theoretical Foundations of Chemical Engineering 48, no. 2 (March 2014): 117–26. http://dx.doi.org/10.1134/s0040579514020109.

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12

Olson, Timothy G. "2.1.1 Defining Lean Systems Engineering Processes and Procedures." INCOSE International Symposium 17, no. 1 (June 2007): 246–57. http://dx.doi.org/10.1002/j.2334-5837.2007.tb02872.x.

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13

Barash, Moshe M. "Manufacturing engineering processes." Journal of Manufacturing Systems 13, no. 3 (January 1994): 235–37. http://dx.doi.org/10.1016/0278-6125(94)90007-8.

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14

van Genuchten, Michiel. "Analysis and improvement of software engineering processes." Information & Management 25, no. 1 (July 1993): 43–49. http://dx.doi.org/10.1016/0378-7206(93)90024-n.

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15

Oppenheim, Bohdan, and Deborah Secor. "Organization of 147 Lean Enablers for Systems Engineering into the 26 INCOSE Systems Engineering Processes." INCOSE International Symposium 21, no. 1 (June 2011): 314–15. http://dx.doi.org/10.1002/j.2334-5837.2011.tb01209.x.

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16

Rouached, Mohsen, Walid Fdhila, and Claude Godart. "A semantical framework to engineering WSBPEL processes." Information Systems and e-Business Management 7, no. 2 (March 4, 2008): 223–50. http://dx.doi.org/10.1007/s10257-008-0081-5.

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17

Granicka, Ludomira H., and Wojciech Piątkiewicz. "Membrane Systems for Biomedical Engineering." Membranes 13, no. 1 (December 29, 2022): 41. http://dx.doi.org/10.3390/membranes13010041.

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The thematic scope concerning membrane systems for biomedical engineering is very wide; it concerns new methods of designing membrane systems for biomedical and biomedical-related environmental processes [...]
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18

Dyer, M., T. Kraly, F. Luppino, and R. Waldron. "Integrating an enterprise's engineering processes." Information and Software Technology 35, no. 6-7 (June 1993): 355–63. http://dx.doi.org/10.1016/0950-5849(93)90006-o.

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19

Towill, D. R. "Successful business systems engineering. Part 1: The systems approach to business processes." Engineering Management Journal 7, no. 1 (1997): 55. http://dx.doi.org/10.1049/em:19970109.

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20

Ebeling, James M. "Engineering Aspects of Recirculating Aquaculture Systems." Marine Technology Society Journal 34, no. 1 (January 1, 2000): 68–78. http://dx.doi.org/10.4031/mtsj.34.1.8.

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Intensive recirculating aquaculture systems utilizing water recirculation and pure oxygen injection are examined in terms of the individual unit processes that are required to handle the wastes generated by fish at stocking densities as high as 120‐150 kg/m3. These unit processes include solid waste removal, nitrification of ammonia and nitrite, aeration or oxygenation, carbon dioxide removal, and control and monitoring systems. Overall system integration is reviewed and an example of a research/commercial intensive recirculating system is presented.
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21

Szelka, Janusz, and Zbigniew Wrona. "Inference processes in incomplete knowledge systems in engineering projects." Budownictwo i Architektura 13, no. 4 (December 11, 2014): 407–15. http://dx.doi.org/10.35784/bud-arch.1875.

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A substantial number of engineering problems can be qualified as heuristic ones. Inference processes, allowing for their solution, are most frequently performed with rule-based expert systems. Such systems, however, are significantly limited by their possibility of inference only if complete knowledge is possessed, which is not always the case in practice (in particular in crisis situations). It is then indispensable to employ other methods and tools. Given the specificity of engineering projects, it seems that case-based reasoning (CBR) is an appropriate solution in this respect. In conjunction with rule-based inference mechanisms, it may constitute a complementary solution, allowing for efficient inference in problem situations in which the level of knowledge completeness varies.
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22

Nehls, Nicole, Tze Sheng Yap, Talya Salant, Mark Aronson, Gordon Schiff, Suzanne Olbricht, Swapna Reddy, et al. "Systems engineering analysis of diagnostic referral closed-loop processes." BMJ Open Quality 10, no. 4 (November 2021): e001603. http://dx.doi.org/10.1136/bmjoq-2021-001603.

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BackgroundClosing loops to complete diagnostic referrals remains a significant patient safety problem in most health systems, with 65%–73% failure rates and significant delays common despite years of improvement efforts, suggesting new approaches may be useful. Systems engineering (SE) methods increasingly are advocated in healthcare for their value in studying and redesigning complex processes.ObjectiveConduct a formative SE analysis of process logic, variation, reliability and failures for completing diagnostic referrals originating in two primary care practices serving different demographics, using dermatology as an illustrating use case.MethodsAn interdisciplinary team of clinicians, systems engineers, quality improvement specialists, and patient representatives collaborated to understand processes of initiating and completing diagnostic referrals. Cross-functional process maps were developed through iterative group interviews with an urban community-based health centre and a teaching practice within a large academic medical centre. Results were used to conduct an engineering process analysis, assess variation within and between practices, and identify common failure modes and potential solutions.ResultsProcesses to complete diagnostic referrals involve many sub-standard design constructs, with significant workflow variation between and within practices, statistical instability and special cause variation in completion rates and timeliness, and only 21% of all process activities estimated as value-add. Failure modes were similar between the two practices, with most process activities relying on low-reliability concepts (eg, reminders, workarounds, education and verification/inspection). Several opportunities were identified to incorporate higher reliability process constructs (eg, simplification, consolidation, standardisation, forcing functions, automation and opt-outs).ConclusionFrom a systems science perspective, diagnostic referral processes perform poorly in part because their fundamental designs are fraught with low-reliability characteristics and mental models, including formalised workaround and rework activities, suggesting a need for different approaches versus incremental improvement of existing processes. SE perspectives and methods offer new ways of thinking about patient safety problems, failures and potential solutions.
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23

Giboney, Justin S., Robert Briggs, and Jay Nunamaker, Jr. "Special Section: Engineering Artifacts and Processes of Information Systems." Journal of Management Information Systems 36, no. 1 (January 2, 2019): 11–13. http://dx.doi.org/10.1080/07421222.2018.1551763.

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24

Ziyatdinov, N. N. "Modeling and Optimization of Chemical Engineering Processes and Systems." Theoretical Foundations of Chemical Engineering 51, no. 6 (November 2017): 889–92. http://dx.doi.org/10.1134/s0040579517060197.

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25

Terzi, Sergio. "Designing complex products with Systems Engineering processes and techniques." Production Planning & Control 27, no. 12 (April 29, 2016): 1039. http://dx.doi.org/10.1080/09537287.2016.1177213.

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26

Siptits, S. O., and N. E. Evdokimova. "Mathematical modeling of management processes in agricultural engineering systems." IOP Conference Series: Materials Science and Engineering 919 (September 26, 2020): 052062. http://dx.doi.org/10.1088/1757-899x/919/5/052062.

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27

BOUFFARON, Fabien, David GOUYON, Dragoş DOBRE, and Gérard MOREL. "Revisiting the interoperation relationships between Systems Engineering collaborative processes." IFAC Proceedings Volumes 45, no. 6 (May 2012): 1517–22. http://dx.doi.org/10.3182/20120523-3-ro-2023.00190.

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28

Tahan, Meir, and Joseph Z. Ben-Asher. "Modeling and analysis of integration processes for engineering systems." Systems Engineering 8, no. 1 (2005): 62–77. http://dx.doi.org/10.1002/sys.20021.

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29

Braatz, Richard D., Richard C. Alkire, Effendi Rusli, and Timothy O. Drews. "Multiscale systems engineering with applications to chemical reaction processes." Chemical Engineering Science 59, no. 22-23 (November 2004): 5623–28. http://dx.doi.org/10.1016/j.ces.2004.09.022.

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30

Grote, C., E. Brinksmeier, and M. Garbrecht. "Distortion engineering in turning processes with standard clamping systems." Materialwissenschaft und Werkstofftechnik 40, no. 5-6 (May 2009): 385–89. http://dx.doi.org/10.1002/mawe.200900464.

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31

Berenbach, Brian, and John Worl. "Requirements Engineering for Large Scale Systems: Processes and Tooling." INCOSE International Symposium 21, no. 1 (June 2011): 2824. http://dx.doi.org/10.1002/j.2334-5837.2011.tb01303.x.

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32

Jang, Yoon-ha, Sae Ryun Ahn, Ji-yeon Shim, and Kwang-il Lim. "Engineering Genetic Systems for Treating Mitochondrial Diseases." Pharmaceutics 13, no. 6 (May 28, 2021): 810. http://dx.doi.org/10.3390/pharmaceutics13060810.

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Mitochondria are intracellular energy generators involved in various cellular processes. Therefore, mitochondrial dysfunction often leads to multiple serious diseases, including neurodegenerative and cardiovascular diseases. A better understanding of the underlying mitochondrial dysfunctions of the molecular mechanism will provide important hints on how to mitigate the symptoms of mitochondrial diseases and eventually cure them. In this review, we first summarize the key parts of the genetic processes that control the physiology and functions of mitochondria and discuss how alterations of the processes cause mitochondrial diseases. We then list up the relevant core genetic components involved in these processes and explore the mutations of the components that link to the diseases. Lastly, we discuss recent attempts to apply multiple genetic methods to alleviate and further reverse the adverse effects of the core component mutations on the physiology and functions of mitochondria.
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33

Gusakov, Alexander, Olga Ilina, Ekaterina Kulikova, and Olga Melikhova. "TOPICAL ISSUES OF SYSTEMS ENGINEERING." JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT 9, no. 3 (September 30, 2003): 214–17. http://dx.doi.org/10.3846/13923730.2003.10531329.

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The article deals with topical issues of systems engineering development which is considered as a scientific-engineering methodology of effective design and functioning of construction systems and intersystem ties that are of great diversity and individuality. The authors investigate the processes of forming and selecting CAD information strategies, norms- and rule-making in construction sphere, methods of macrodesign of construction systems.
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34

Greene, Melissa T., Richard Gonzalez, and Panos Y. Papalambros. "Measuring Systems Engineering and Design Thinking Attitudes." Proceedings of the Design Society: International Conference on Engineering Design 1, no. 1 (July 2019): 3939–48. http://dx.doi.org/10.1017/dsi.2019.401.

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AbstractSystems engineering and design thinking have been widely seen as distinctly different processes, systems engineering being more data-driven and analytical, and design thinking being more human- centred and creative. We use the term ‘design thinking’ to encompass the plurality of human-centered design processes that seek to unpack the core values behind design decisions. With the increased awareness that both systems engineering and design thinking need each other, the effects of a possibly persisting distinction on engineers’ attitudes toward these two processes are not well understood. In this paper, we describe the development and validation of a scale for measuring individual attitudes about systems engineering and design thinking. Thematic analysis of engineering and design literature is used to derive a Likert scale reflecting these attitudes. We use exploratory and confirmatory factor analysis to test and confirm this two-factor thematic representation, resulting in a 9-item Systems Engineering and Design Thinking Scale measure of attitudes.
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35

OUERTANI, MOHAMED ZIED. "ENGINEERING CHANGE IMPACT ON PRODUCT DEVELOPMENT PROCESSES." Systems Research Forum 03, no. 01 (September 2009): 25–37. http://dx.doi.org/10.1142/s1793966609000043.

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36

Vasin, S. A., and E. V. Plakhotnikova. "Energy Processes in Complex Systems." Russian Engineering Research 38, no. 10 (October 2018): 785–89. http://dx.doi.org/10.3103/s1068798x18100167.

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37

Muehlhause, Mathias, Nico Suchold, and Christian Diedrich. "Application of semantic technologies in engineering processes for manufacturing systems." IFAC Proceedings Volumes 43, no. 4 (2010): 54–59. http://dx.doi.org/10.3182/20100701-2-pt-4011.00011.

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38

Inukai, Toshihiro, Hironori Hibino, and Yoshiro Fukuda. "DISTRIBUTED SIMULATION ENVIRONMENT TO EVALUATE MANUFCTURING SYSTEMS ALONG ENGINEERING PROCESSES." IFAC Proceedings Volumes 39, no. 3 (2006): 77–82. http://dx.doi.org/10.3182/20060517-3-fr-2903.00047.

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39

Hagemans, KL. "Vacuum systems and processes from the viewpoint of software engineering." Vacuum 38, no. 8-10 (January 1988): 711–18. http://dx.doi.org/10.1016/0042-207x(88)90448-4.

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40

BENNEYAN, JAMES C., and CLAIRE BOND. "SYSTEMS ENGINEERING APPROACHES FOR IMPROVING REUSABLE MEDICAL EQUIPMENT REPROCESSING PROCESSES." International Journal of Innovation and Technology Management 10, no. 03 (June 2013): 1340009. http://dx.doi.org/10.1142/s0219877013400099.

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Hospital reusable medical equipment (RME) includes any items that are intended to be reprocessed and reused indefinitely, including surgical instruments, dental equipment, endoscopes, and others. Such equipment represent a significant portion of a hospital's inventory costs and recently have generated significant patient cross-contamination concerns due to reprocessing cleaning failures. This paper discusses recent applications of industrial and systems engineering (ISyE) methods within healthcare organizations to help manage, understand, and improve RME processes, including quality control (QC), reliability, patient safety, facility layout, queuing networks, and inventory management models. Several examples demonstrate the value of these approaches for improved reprocessing management of RME technology.
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41

Murdoch, John, John A. McDermid, and Philip Wilkinson. "4 Tailoring Generic Systems Engineering Processes: an agent-oriented method." INCOSE International Symposium 9, no. 1 (June 1999): 845–53. http://dx.doi.org/10.1002/j.2334-5837.1999.tb00247.x.

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42

Witte, Craig S. "3.6.2 Successful Integration of Systems Engineering and Program Management Processes." INCOSE International Symposium 14, no. 1 (June 2004): 650–61. http://dx.doi.org/10.1002/j.2334-5837.2004.tb00524.x.

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43

Pickard, Andrew C., and Andrew J. Nolan. "2.2.1 When is Enough Enough? Tailoring Processes in Systems Engineering." INCOSE International Symposium 21, no. 1 (June 2011): 158–69. http://dx.doi.org/10.1002/j.2334-5837.2011.tb01194.x.

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44

Fedaghi, Sabah Al, and Abdulaziz AlQallaf. "Modelling and control of engineering plant processes." International Journal of Applied Systemic Studies 8, no. 3 (2018): 255. http://dx.doi.org/10.1504/ijass.2018.096122.

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45

FARIA, JOSE, and EUSEBIO NUNES. "RELIABILITY ENGINEERING OF LARGE JIT PRODUCTION SYSTEMS." International Journal of Reliability, Quality and Safety Engineering 19, no. 03 (June 2012): 1250011. http://dx.doi.org/10.1142/s0218539312500118.

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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.
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46

Misnik, Anton Е. "Metagraphs for ontological engineering of complex systems." Journal Of Applied Informatics 17, no. 2 (March 31, 2022): 120–32. http://dx.doi.org/10.37791/2687-0649-2022-17-2-120-132.

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The article deals with the issues of ontological engineering of complex systems. Ontological engineering includes the processes of designing and building ontologies, technologically combining object-oriented and structural analysis. Ontological engineering aims to ensure the adoption of high-quality management decisions by increasing the level of integration of the necessary information, improving search capabilities in databases and knowledge bases, providing the possibility of joint processing of knowledge based on a single semantic description of the knowledge space. This process is carried out within the framework of the proposed approach to managing complex systems. The ontology obtained as a result of engineering is subject to the requirements of convenience and flexibility, which is necessary for modeling system processes and ensuring the functioning of information and analytical processes in a complex system. The application of ordinary graphs, hypergraphs and metagraphs in ontological engineering is described. The use of metagraphs in the construction of hierarchical ontologies is substantiated. Metagraphs are considered as the basis for building an applied ontology of a complex system. A modification of the metagraph is proposed, which makes it possible to include events and data processing methods in the ontology. Such a modification integrates the process component into the ontological model of the system as an integral part of it, which makes it possible to flexibly and with less time to form process models based on the metagraph subgraphs of the general ontological model. An approach and an example of the implementation of the software-instrumental environment of ontological engineering and further construction of models of processes of a complex system are described. The technology used to implement the ontology in the PostgreSQL database management system and the database structure for storing the ontology are described
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47

Rangan, Ravi M., and Bipin Chadha. "Engineering Information Management to Support Enterprise Business Processes." Journal of Computing and Information Science in Engineering 1, no. 1 (January 1, 2001): 32–40. http://dx.doi.org/10.1115/1.1353845.

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Product definition information drives many business processes, yet its management at a coarse level (documents and files) precludes efficient automation and decision support. Information management at finer levels of granularity realizes the full potential of computable representations. This paper presents an industry oriented perspective of engineering information management (EIM) technologies and implementations and offers classifications of information systems as it relates to EIM systems and business processes. The concept of structured business objects that encapsulate the information and business-process definition at appropriate levels of granularity to support enterprise process dynamics is introduced. This provides a key construct to model the unique, and sometimes opposing, process perspectives within the enterprise. The paper then discusses key EIM and integration issues and future directions.
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48

WEIDE, BRUCE W., and SAM DEFAZIO. "A FRAMEWORK FOR MODELING SOFTWARE ENGINEERING PROCESSES." International Journal of Software Engineering and Knowledge Engineering 03, no. 03 (September 1993): 351–68. http://dx.doi.org/10.1142/s0218194093000161.

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Summary—Software engineering processes must be understood to be managed effectively. It is important to go beyond purely metaphorical and descriptive methods to achieve such understanding. This paper proposes a framework, based on dynamic feedback control systems, for building potentially quantitative models of software engineering processes. It then uses this framework to explore some important characteristics of quantifiable outputs of such processes, including observability, measurability, independence, (near) continuity, and (near) monotonicity. General Terms—Software engineering, process modeling.
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49

JAROS, P., M. SOBOTKA, and R. HRACH. "Relaxation processes in MIM systems." International Journal of Electronics 73, no. 5 (November 1992): 829–31. http://dx.doi.org/10.1080/00207219208925717.

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50

BLAKE, M. BRIAN, and LISA SINGH. "SOFTWARE ENGINEERING FOR WEB SERVICES WORKFLOW SYSTEMS." International Journal of Software Engineering and Knowledge Engineering 18, no. 02 (March 2008): 157–78. http://dx.doi.org/10.1142/s0218194008003593.

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Service-oriented computing (SOC) suggests that many open, network-accessible services will be available over the Internet for organizations to incorporate into their own processes. Developing new software systems by composing an organization's local services and externally-available web services is conceptually different from system development supported by traditional software engineering lifecycles. Consumer organizations typically have no control over the quality and/or consistency of the external services that they incorporate, thus top-down software development lifecycles are impractical. Software architects and designers will require agile, lightweight processes to evaluate tradeoffs in system design based on the "estimated" responsiveness of external services coupled with known performance of local services. We introduce a model-driven software engineering approach for designing systems (i.e. workflows of web services) under these circumstances and a corresponding simulation-based evaluation tool.
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