The Impact of Technology Insertion on Organisations

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HFIDTC/2/12.2.1/1 Version 3 / 21 November 2007 One advantage <strong>of</strong> using BBNs is that sharing an understanding among many heterogeneous stakeholders (procurement, design, manufacturing, etc.) using both qualitative and explicit data is a possibility. <strong>The</strong> approach followed in this work is to use decision analysis to decide design refresh content for candidate design refresh dates generated by the MOCA tool. This approach enables the consideration <strong>of</strong> all the decisions affecting variables at the same time. Aspects such as the availability <strong>of</strong> a new part to replace the old part, the available stock <strong>of</strong> the old part, the performance and reliability change due to part changes, impacts on the system s<strong>of</strong>tware due to hardware changes, requalification that may be triggered by part changes, etc can be incorporated. This approach ensures that users consider both dimensions <strong>of</strong> optimisation, i.e., date <strong>of</strong> the design refresh along with what is changed at the design refresh. <strong>The</strong> data associated with utility nodes represent the inputs from various stakeholders, i.e., ‘customer-directed value’. Other tools which have been developed to support practitioners in technical aspects <strong>of</strong> technology insertion include: 10.2.1.2 Simulation Assisted Reliability Assessment (SARA) Simulation Assisted Reliability Assessment (SARA) is another CALCE approach to supporting technology insertion practitioners. SARA has been developed to use ‘physics <strong>of</strong> failure’ based principles and s<strong>of</strong>tware to assess whether a part or system can meet defined life cycle requirements [215]. This tool takes into account technical component requirements based on materials, geometry, and operating characteristics. <strong>The</strong> SARA s<strong>of</strong>tware ‘can be used to assess life expectancy <strong>of</strong> electronic hardware under anticipated life cycle loading conditions, as well as under accelerated stress test conditions’. <strong>The</strong> SARA s<strong>of</strong>tware toolkit is designed to help engineers predict and manage technology component reliability in technology insertion programmes. This s<strong>of</strong>tware does not consider organisational or human factors that influence design decisions. 10.2.1.3 Concept Analysis and Design Evaluation Toolkit (CADET) Numerous spacecraft technology development programs are sponsored by the DoD and NASA with the goal <strong>of</strong> enhancing spacecraft performance, reducing mass, and reducing cost. Bearden et al [216] found that it is <strong>of</strong>ten the case that technology programs, in the interest <strong>of</strong> maximising subsystem-level performance and/or mass reduction, do not anticipate synergistic system-level effects. To address these issues, a concept analysis methodology and s<strong>of</strong>tware toolset was developed. <strong>The</strong>se tools, collectively referred to as the concept analysis and design evaluation toolkit (CADET), were developed in order to try to facilitate technology selection, and identify associated effects on cost, risk and performance at the system and subsystem level. CADET claims to enable: (1) quick response to technical design and cost questions (2) assessment <strong>of</strong> the cost and performance impacts <strong>of</strong> existing and new designs/technologies (3) estimation <strong>of</strong> cost uncertainties and risks. <strong>The</strong>se capabilities aid mission designers in determining the configuration <strong>of</strong> remote sensing missions that meet essential requirements in a cost-effective manner. 57
HFIDTC/2/12.2.1/1 Version 3 / 21 November 2007 <strong>The</strong>se tools focus on technical and cost aspects <strong>of</strong> technology insertion decision making, but do not consider wider organisational implications. 10.2.1.4 Aviation System Risk Model (ASRM) <strong>The</strong> Aviation System Risk Model (ASRM), a Probabilistic Decision Support System (PDSS), is being developed [217] to assist NASA program managers in evaluating new technologies that are intended to lower the fatal aircraft accident rate. This decision support system utilises the method <strong>of</strong> case-based reasoning in which case studies <strong>of</strong> specific accidents are analysed and modelled to assess reduction through the insertion <strong>of</strong> appropriate technologies. <strong>The</strong> analytical approach used in this research is a systematic method for modelling aircraft accidents and assessing risk reduction. <strong>The</strong> analytic modelling approach consists <strong>of</strong> the following stages: [1] Describing a case-based scenario and determining the events involved in the occurrence <strong>of</strong> the accident/incident. [2] Identifying the causal factors (nodes) present in these events using the Human Factors Analysis and Classification System (HFACS) taxonomy. [3] Construction <strong>of</strong> an influence diagram depicting the interrelationships among these nodes. [4] Building a BBN propagated with conditional probabilities. Probabilities are based on a combination <strong>of</strong> statistical frequencies from the National Transportation Safety Board (NTSB) database and judgements from subject matter experts. [5] Inserting the relevant technologies/interventions into the model <strong>of</strong> the particular case, attaching each to a causal factor. [6] Assessing the relative risk <strong>of</strong> the particular case and the reduction in risk resulting from varying combinations <strong>of</strong> technology insertions. <strong>The</strong> following model (see Figure 9) depicts the causal factors identified in an accident case study (Air Ontario 1363 [218]) and the interactions among them. 58
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The Impact of Technology Insertion on Organisations

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