3rd CRECOS Seminary. Espoo, FI: Aalto University, 11-12 November 2010 1
IS SYSTEMS ENGINEERING COMPLIANT WITH “SYSTEMISM”? Jean-Pierre MICAËLLI Université de Lyon, INSA Lyon, ITUS Research Team, UMR CNRS 5600 Environnement, Ville, Société 1, rue des Humanités – F-69621 Villeurbanne Cedex – jean-pierre.micaelli@insa-lyon.fr
I. INTRODUCTION Systems Engineering (SE) can be considered as a dashing forty. Born in the military domain in the 1960s to manage weapons design projects [1], it has spread in a growing number of sectors: aircraft, aerospace, software or automotive industries, scientific instrumentation, synthetic biology or chemistry [2]… These sectors share a same characteristic. Their products and the way they are designed gain in complexity. Thus, there is nothing in common between the empirical and heroic way Henry Ford (1863-1947) has designed his famous Model T [3] and how hybrid cars are now developed with the help of numerical models, CAD systems, digital mock ups, refined project or teams management methods... New tools, organizations, processes, skills, job positions... are required to design complex “artifacts” [4], i.e designed objects, anthropic environments, organizations, controlled natural environments (e.g dammed rivers or seashores) [5], living organisms... Many experienced practitioners belonging to different sectors or countries try to develop a framework managing such a complex design. Therefore, it is not surprising that SE led to the formation of a worldwide “community of practice” [6]: the International Council on Systems Engineering (INCOSE, 1990). SE promoters also propose international SE standards, e.g. ISO 15288. These standards do not contain working rules. They are based on concepts. For example, IEEE 1220 (1995) standard presents SE as “an interdisciplinary collaborative approach to derive, evolve, and verify a life-cycle balanced system solution which satisfies customer expectations and meets public acceptability”. This definition mentions non-trivial concepts such as interdisciplinary approach, collaboration, system, solution, life cycle... More recently, SE community offers a language codifying SE domain knowledge and specifying ad-hoc software applications. This specific domain language is called SysML (Systems Modeling Language) [7]. “The origin of the SysML initiative can be traced to a strategic decision by the (…) INCOSE Model Driven Systems Design workgroup in January 2001 to customize the Unified Modeling Language (UML) for systems engineering applications” [7]. All the facts mentioned above show that SE is not a compendium of good practices. Its main purpose is a conceptual one. SE is helpful to conceptualize as systems complex artifacts, be they designed product or design organizations. If SE framework is explicitly systemic, my hypothesis is that it is not systemic enough! I would like to show that current SE framework does not fully comply with what Quantum Physics epistemologist Mario Bunge (b. 1919) calls “Systemism” [8]. To address this question, the remainder of this communication is structured as follows. Section II presents Bunge's “Systemism”. Section III presents the way it can be used to identify current SE framework epistemological weaknesses. Section IV suggests
some ways to reduce them.
II. WHAT IS “SYSTEMISM”? Epistemology can be defined as the theory of knowledge. It tries to answer to the following questions: what do we know? How do we know? The first question is of “gnoseology” (from gnosis, knowledge) [9]. It can help to discriminate different types of knowledge, e.g scientific knowledge to folk's one, scientific knowledge to technological one [5], generic knowledge to specific one, formal knowledge to substantial one, sciences to “pseudosciences” [8]... When ones builds an “formal ontology” [10], one proposes a structured representation of a gnoseology. Epistemology is also focused on the way knowledge is represented, produced, debated, validated, generalized, challenged, specialized, institutionalized, abandoned... It also takes into account the individuals, the communities, the institutions involved in the perpetuum mobile of knowledge production. For epistemologists, Homo sapiens sapiens is not only the worthy successor of Homo faber. He is also a “Homo quaerens” [11]. He will never stop to ask new questions. Knowledge production is an open-ended process and an endless process. For epistemologists, knowledge is only based on knowledge. More precisely, every gnoseology is based on a Weltanschauung, i.e a global vision of the world (Cosmos, Universe, Reality...) [8]. For example, “Mechanicism” is an epistemology based on the assumption that the world is like a gigantic clock [8]. Knowing subject's purpose consists in discovering its structure and the exact laws explaining how it behaves (its mechanisms). The knowing subject uses his reason, i.e his reasoning mechanisms, to have a clear vision of these laws. He uses mathematics to formalized them. He collects empirical data to underpine them. Mechanicist theoricists (Descartes, Leibniz, Laplace, Kant...) have founded “ratio-empirical” sciences [8]. They have defined modern epistemological concepts such as knowing subject, experiment, data, law, cause, probability, formalization... While admitting the complementary aspect of empirical knowledge and abstract knowledge, Mechanicism remains a monadist and a dualistic epistemology. All entities Mechanicism takes into account are conceptualized as monadic units. For example, a law exists by itself. It can be studied as an autonomous whole. For dualist Mecanicist, it exists irreducible differences between epistemological entities. A law is not a datum. More generally, the knowing subject differs from the knowable world, a formal language from an empirical tool, a abstract knowledge from a practical one, the mind from the body... Mechanicism was challenged by Quantum Physics [12]. Its epistemologists have replaced this old-fashioned epistemology by a “relational epistemology” [12]. It stands that it does not exist independent, “wandering” or “motherless” data, concepts, theories, scientific domains,
2 J-P.Micaëlli: Is SE compliant with “Systemism”?
tools, knowing subjects [8]… Every epistemological entity is related to another ones. The relation is our first knowable reality [12]. Making relations between scattered is the one the way one follows to creatively understand, design or build a new reality [13]. For relational epistemologists, knowledge is not seen as a set of isolated islands, but as an epistemic archipelago. For example, a Mechanicist theorists conceptualizes time as a set of separate moments {t0,t1,t2,...,tn}. As a dualist thinker, he postulates that time differs from space. If one maps the space and the time separate domains, then one obtains the Newtonian scene within mechanical events appear, e.g the trajectory of a mobile. For relational epistemology, time is a relational phenomenon having global or macroscopic properties. It refers to a material, but nonaddressed reality, giving coherence to a succession of states and then allowing us to think in terms of causality or futurity [14]. Moreover, times is closely intricated to other physical domains. If one writes {t0,t1,t2,...,tn}, then one implicitly expresses a macrostructure which can be graphically represented by a graph: – associating nodes (the moments) by oriented arcs representing causality and moments ranking. Each period of time is a subgraph. Each extension of a period following recurrent reasoning is a graph extension, – related to other graphs representing other physical domains. Then, physical phenomena are expressed by knoting complementary graphs. None of them can be separated. All of them are required to have a global understanding, description or modeling of the phenomenon under study. “Systemism” can be seen as an avatar of relational epistemology [8]. “Systemism” inherits the results of the second generation cybernetics [4] [9]. It defines the “cosmos as a supersystem composed by several changing systems, and conceptualizes the knowledge one has about Reality as a supersystem of data, hypothesis, standards or methods (…) It postulates that every concrete object or idea is either a system, either a part of a system” [8]. “Systemism” stands that every system possesses the following four attributes: – it associates several components, – it has an external environment, then a frontier or a “skin” [4] which gives it distinguishably, – it has a structure, be it an “endostructure” or a “exostructure” [8]. The endostructure is usually described as a “semi-decomposable” architecture combining several modules and layers [4]. The exostructure refers to the interfaces the system has with its external environment, – it has a “mechanism” [8], that is a set of processes explaining its states, transitions, dynamics, behaviors, evolution... In the case we have previously mentioned, those systemic postulates mean that the time is a physical domain conceptualized as: – a set of moments, – a domain distinguished from the other physical domains dynamic analysis requires, – an endostructure, i.e a bounded set of ranked moments, and an exostructure, i.e a domain closely connected to other physical domains, – a process explaining events distinguishability (the
event at t1 is not the event at t2) and causality (if t1 is the cause of t2, then t1 precedes t2). “Systemism” has at least three epistemological consequences. Firstly, if a system is an entity by definition, i.e an abstract thing, it is necessary to not forget that it is based on material or empirical backgrounds. If not, one can imagine the pure system of everything, that said: the system of nothing. Bunge's “Systemism” belongs to realism, no to idealism or modern social constructivism [8]. But as a Quantum Physics epistemologist, Bunge postulates that reality does not give by itself, freely and completely, its whole properties. Costly devices such as experiences, equipments, models, statistical data, and bounded knowing subjects are required to depict it [11]. Object systemic knowledge requires a whole epistemic system associating all the mentioned entities. That means that a system is not an immediate, pure and boundless entity. It is a built model of a given reality. It requires existing, contextualized, contingent and concrete knowing subject [9], knowledge, methods, tools... For example, Evolution was recognized as a scientific phenomenon at the end of the nineteen century, but it was conceptualized as a system when the “Neo-darwinian Synthesis” occurred [15]. It gave a systemic viewpoint on evolution, involving intricate processes related to genes, individuals, populations, behaviors... [15]. Thus, advances in Biology, Biochemistry, Bio-instruments... have facilitated a systemic conceptualization of Evolution. Secondly, if one defines a knowable object as a system, then one must admit that his knowledge about this object is also a system. Bunge illustrates this point by mentioning the case of Neuroscience [8]. This last one is based on the association of separate domains: neurophysiology, neurology, psychology, psychiatry, computer sciences, image processing… In this case, interdisciplinary knowledge describing and explaining cognitive material processes is not only a slogan. It is a way of practicing a fruitful science. In a previous work, I defined an “epistemic complexity” criterion [16] characterizing such a science. A complex knowledge associates several equal domains – then viewpoints – in a non-trivial way [16]. It combines monism and pluralism. The system under study is unique by definition: everyone understands it as a whole (ontological monism). But one locally analyzes it by focusing on particular viewpoint (methodological monism), and globally analyzes it by trying to knot viewpoints (methodological pluralism). None of them is dominant (methodological pluralism). Thirdly, a system can be studied following top-down or bottom-up approaches [8]. In the first case, one decomposes the system in several layers containing black boxes, to have an external or global viewpoint. This way of thinking reduces the level of the “cognitive cost” [4] [16]. In the second case, one synthesizes the local knowledge about a set of white boxes belonging to a same layer, to identify systemic or emerging phenomena. Synthesis is not the specular face of decomposition. It seems to require higher cognitive abilities. Bunge's “Systemism” mainly refers to Physics, then natural sciences [8]. However it may have an echo in Systems engineering, which belongs to “technological knowledge” [5].
3rd CRECOS Seminary. Espoo, FI: Aalto University, 11-12 November 2010 3
III. FROM “SYSTEMISM” TO SYSTEMS ENGINEERING
Epistemological foundations of the current SE framework can be improved.
By definition SE is systemic. If one reads the thesaurus wrote by the French Society of SE (AFIS) in October 2004 [17], one can count in this 48 pages document more than 90 occurrences of “system”! This last concept is also frequently presented in SE standards. For example, ISO 15288 writers define it as “combination of interacting elements organized to achieve one or more stated purposes (…) The term Systems defines a “concept” characterized by a set of properties such as the function provided, external interfaces, architecture(s)...” [17]. They add that SE framework refers to a wide set of systems: the system of interest, the enabling system, the cooperating or competing systems, the operational system... These systemic definition is largely accepted by engineers. SE or even SysML frameworks offer concepts, ontologies, diagrams to describe the “system of interest” (ISO 15288), its operational environment, its components, its structure, its functional behavior and its underlying physical laws (e.g SysML parametric diagrams [7])... SE standards also offer concepts or activity diagrams describing design processes. Nevertheless, SE promoters miss some key questions “Systemism” points out. The first epistemological questions concern the knowing subject. Who is the knowing subject identifying the system of interest? Is it the customer, the designer, the design manager, the project manager...? Have they the same viewpoints? Does an overhang viewpoint of the system of interest exist? If not (if SE knowledge is complex), what kind of knowledge architecture SE requires? How one can navigate from a viewpoint to another one? Does SE facilitate relation-based and exploration-based invention or innovation processes? SE promoters have no answer to these questions. The ontology of System INCOSE SE Handbook [17] proposes does not mention any design actor. SE promoters do not clarify the contribution other design, engineering, social or scientific domains may offer. They assert their approach is a collaborative one, but they do not go further in this question. In SE framework, we do not know who collaborates with who. SE promoters believe that it exists an omniscient designer, despite this idea was challenged by the sciences of design [4] [16]. The second set of epistemological questions concerns SE framework relevant scope. SE is an integrative framework. It concerns all kind of systems: designed products, design organizations... Whatever the case, SE promoters propose guidelines for system decomposition, differentiation or embodiment. Nothing is said about the validation criteria of such systemic operations. How can one be sure that the identified system is the "good" system? What are the “stop rules” [4] defining a satisfying system decomposition, synthesis or embodiment? Is the identified system a generic one or a specific one? If it is a generic system, then how one proceeds to extend it to domains which are not taken into account by current SE framework? Why SE specialists do not take into account phenomena embodiment designers (shape, form of the system...), natural scientists (environment, evolutionary processes...) or social scientists (appropriation or artefact-based learning process, use...) define as systems? The idea of a possible boundless SE framework is not questioned. The critics I have made are very hard. However I do not want to conclude this communication on a pessimistic note.
IV. IMPROVE SYSTEMS ENGINEERING SYSTEMICITY The first way to improve those foundations consists in defining a clear gnoseology of the domain. When someone mentions the term “system” what is its acceptance in SE context? The first precaution to be taken is to contextualize this acceptance. I suggest to define SE as the way current upstream designers of complex artifacts conceptualize the routine part of their practice, be it product-focused or organization-focused. SE is not a monadic unit containing all design managerial or technical knowledge. It complies with a new “design paradigm” [18], i.e way of practicing, conceptualizing, learning design “activity” [19], we have called “abstract design” [20]. In this paradigm, upstream designers do not prototype the solution earlier as possible and as realistically as possible. They can not do that because they have irreducible “bounded” [4] knowledge about its details. However, they are supposed to have enough knowledge from empirical experience or modeling techniques to identify the abstract attributes of the artifact, and to replicate them from one project to another one. Therefore SE is not seen as an expression of an omniscient designer's will. It is considered as a bounded designer's contextualized response using available systemic concepts or tools, e.g diagrams [9] or object-oriented language [16]. The models upstream designers build in reference to this monist entity called system are not generative applications. They do not automated the several embodiment designs a complex artifact development requires. They just play the role of a vehicular language. They facilitate the cognitive convergence of several design actors involved in a common project, then “working community” [19]. Thus, relations between abstract SE models and realistic models is not trivial. They are based on non-trivial processes by which the artifact is translated to one epistemic world (concrete vs. abstract) to another one (abstract vs. concrete). Abstraction processes outcome consists in a translation of concrete artifact properties into abstract characteristics, e.g organ to function, particular solution to solutions family or line, “initial” process to “managed” one [21]... Concretization process is the reciprocal one. Fig.2 shows a possible SE framework ontology compliant with “Systemism”. Design _Activity
is_a
is_a
Solution has
Relational_ focuses Epistemology
Design _Paradigm is_a
Relations
is_part_of
Systemism
supports
Systems_ Systems_ Engineering Engineering
realizes
Upstream Designer
supports
focuses
supports
Design_Working _Community
Abstract_ Design_ Routine
System has
produces codifies
Concrete -Attribute embodies
is_a
Abstract _Design
Abstract _Model
Epistemic_ Activity
is_a
is_a
requires
Activity
uses
Abstract _Attribute abstracts
is_a is_part_of
Design_ Actor
Fig.1. Possible SE Framework Ontology.
is_a
Tiers
focuses
4 J-P.Micaëlli: Is SE compliant with “Systemism”?
Of course, the previous figure is a global description of SE. Many questions I mentioned above remain unanswered. The ways a system should be bounded, decomposed, differentiated, or extended remain obscure. But after all, SE is only forty years. Fourth decades are not a long time to build a well-based knowledge domain.
VI. REFERENCES [1] [2]
[3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18]
[19] [20]
[21]
S.C. Cook, Ferris T.L.J., 2007. Re-evaluating Systems Engineering as a Framework for Tackling Systems Issues. Systems Research and Behavioral Science, 24(2), pp.169-181. É. Bonjour, S. Deniaud, J-P. Micaëlli, 2009. Conception Complexe et Ingénierie Système. In: S. Aït-el-Hadj, V. Boly (Dir.), Les Systèmes techniques : lois d’évolution et méthodologies de conception. Paris, F: Hermès, pp.83-101. H. Ford, 1922. My Life and Work. Available on: http://www.gutenberg.org. H-A. Simon, 1997. The Sciences of the Artificial. Cambridge, MA: MIT Press (third edition). M. Bunge, 1985. Treatise on Basic Philosophy. Volume 7: Philosophy of Science and Technology. Dordrecht, NL: D.Reidel Publishing Company. E. Wenger, R. McDermott, W-M. Snyder, 2002. Cultivating Communities of Practice: A Guide to managing Knowledge. Boston, MA: Harvard Business School Press. Object Management Group (OMG), 2006. Systems Modeling Language Specification - Final Adopted Specification. November. M. Bunge, 2004. Matérialisme et Humanisme : Pour surmonter la crise de la pensée. Montréal, PQ: Liber. J-L. Le Moigne, 1995. Les Épistémologies constructivistes. Paris, F: Presses Universitaires de France. R-T. Gruber, 1995. Toward principles for the design of ontologies used for knowledge sharing, International Journal of Man-Computer Studies, Vol 43, pp.907-928. N. Rescher, 1999. The Limits of Science. Pittsburgh, PN: Pittsburgh University Press. M. Bitbol, 2010. De L'Intérieur du monde, pour une philosophie et une science des relations. Paris, F: Flammarion. J. Forest, M. Faucheux, 2008. Thinking Creative Rationality. 1st CRECOS Seminary. Espoo, FI: TKK, 10-11 September, 2p. É. Klein, 2009. Le Facteur temps ne sonne jamais deux fois. Paris, F: Flammarion. S. Jay Gould, 2002. The Structure of the Theory of Evolution. Boston, MA: Harvard University Press. J-P. Micaëlli, J. Forest, 2003. Artificialisme : Introduction à une théorie de la conception. Lausanne, CH: Presses Polytechniques et Universitaires Romandes. Association Français d'Ingénierie Système (AFIS), 2004. Glossaire de base de l'Ingénierie Système. Paris, F: AFIS, 48p. R. Stankiewicz, 2000. The Concept of “Design Space”. In: J. Ziman (Ed.), Technological Innovation as an Evolutionary Process. Cambridge, UK: Cambridge University Press, pp.234-247. Y. Engeström, 1987. Learning by Expanding: An ActivityTheoretical Approach to Developmental Research. Helsinki, FI: Orienta Konsultit. É. Bonjour, S. Deniaud, D. Loise, J-P. Micaëlli, 2009. L'Ingénierie Système fondée sur les modèles, clef de voûte de la conception abstraite? Ingenium Research Seminary. Paris, F: CNAM, 3-4 December, 6 p. Software Engineering Institute (SEI), 2008. Capability Maturity Model & Integration (CMMI) Specification v.1.2. Pittsburgh, PN: Carnegie Mellon University.