In complex sociotechnical systems, cognitive and social humans use technology to make sense of situations when making decisions. These elements make sociotechnical systems difficult to develop. A modelling and assessment methodology for systems engineering is required to understand the sociotechnical system's behaviour and underlying structure. Modelling captures the dynamic interaction, as well as the effect of humans in a complex environment. Cognitive Work Analysis and System Dynamics are two complementary approaches applied in mutual support within this context. The objective of this paper is to demonstrate a modelling methodology for complex sociotechnical systems, in order to support the systems engineering process. OPSOMMINGIn komplekse sosio-tegniese stelsels, gebruik kognitiewe en sosiale mense tegnologie om situasies te verstaan en besluite te neem. Hierdie elemente maak sosio-tegniese stelsels moeilik om te ontwikkel. 'n Modellering en assessering metodologie vir stelselingenieurswese is nodig om die gedrag van die sosio-tegniese stelsel en onderliggende struktuur te verstaan. Modellering implementeer die dinamiese interaksie sowel as die effek van die mens in 'n komplekse omgewing. Kognitiewe werkanalise en Stelseldinamika is twee aanvullende benaderings wat binne hierdie konteks toegepas is in wedersydse ondersteuning. Hierdie artikel demonstreer 'n modellering metodologie vir komplekse sosiotegniese stelsels om die stelselsingenieurswese proses te ondersteun. INTRODUCTIONThe development of complex sociotechnical systems (STS) often consists of integrating new technology into existing systems through the application of systems engineering (SE) processes. Standard SE processes can struggle with complex STS, which exhibit dynamic behaviour as many unintended or unpredicted consequences may be experienced. The new artefact often leads to new task possibilities that evolve user requirements [1]. To overcome these difficulties, SE can apply modelling to explore structural, functional, and operational elements of the problem and solution space [2].STS theory, as developed by Trist [3], provides a framework for modelling and analysing complex systems. STS consists of humans applying technology to perform work through a process within a social structure (organisation) to achieve a defined objective [4,5]. Work can become complex due to dynamic interaction between the people themselves, between people and technology, and between people and the environment.The central aim of this paper is to demonstrate a modelling methodology for complex STS in support of the SE process. First, some background will be provided on the development of the modelling methodology before the model is demonstrated.
Systems Engineering techniques and approaches are applied to design and develop solutions for complex problems. Information and Communication Technology systems can be complex to develop where the impact of new technology is not always understood as humans can apply them different than intended. This necessitates the application of a Sociotechnical System framework to analyze the possible impact of a new technology . A rigorous and valid experimentation approach is required to analyze system behaviors in support of Systems Engineering efforts, which is difficult with complex Sociotechnical Systems. Cognitive Work Analysis and SystemDynamics are two complementary approaches that can be applied within this context. The products of these methods assist in defining the hypothesis required for experimenting with the new technology.
Abstract. Due to high cost of defence systems and the advent of multi-role military platforms, defence forces can no longer replace old systems with similar newer systems, but need to effectively and continually re-evaluate their defence capability requirements to optimise the utilisation of current and future systems. The "cradle-to-grave" System Life Cycle (SLC) process underpinning the Department of Defence (DOD) Acquisition Policy is based on four consecutive phases, namely Planning, Acquisition, Deployment and Disposal. This programme-centric approach is prone to disjunction between capability requirements, present systems and future systems, and often neglects sufficient emphasis on the requirements definition activity. This paper suggests that System of Systems Engineering (SoSE) combined with a "cradle-to-cradle" Capability Life Cycle (CLC) process can provide junction between current systems in operation and future systems by taking an integrative, capability-centric approach toward the phasing out and renewal of systems. The SLC and CLC processes are unified by four Systems of Systems (SoS) functions, namely Joint Concept Development and Experimentation, Joint Architecture Management, Joint Knowledge Management and Joint Operational Force Employment. Through this approach it is observed that the SLC Disposal phase does not necessarily follow on the Deployment Phase, but in actual fact becomes part of the Planning Phase. It is contended that sound Systems Engineering (SE) principles combined with SoSE and the CLC process offer a superior approach toward capability development and sustainment, resulting in a more cost-effective (smaller and optimised) defence capability.
Abstract. Different Systems Engineering techniques and approaches are applied to design and develop complex sociotechnical systems for complex problems. In a complex sociotechnical system cognitive and social humans use information technology to make sense of a situation in support of decisions. The complex dynamic system elements, their interaction and, the complex environment make sociotechnical systems difficult to develop. A modelling and assessment methodology in support of the Systems Engineering process is required to understand the sociotechnical system's behaviour and underlying structure. It must capture the dynamic interaction as well as the effect of humans performing work in a complex environment. Cognitive Work Analysis and System Dynamics are two complementary approaches that can be applied in support of each other within this context.
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