Value based development of medical scanner fault service knowledge compliant with design controls

Current manufacturing composition is moving away from traditional areas towards knowledge-intensive high value goods and services. Medical scanners represent a market with a significant proportion of the value coming from services. Managing the development and quality of intangible services is an important activity for manufacturers.;The efficient development of knowledge-based service for medical scanners is challenging due to several factors. The main factors include need for: (i) regulatory compliance of medical scanners service; (ii) economic justification of the necessary knowledge; (iii) clear mapping of requirements into engineering specifications; and (iv) verification and validation of the service knowledge.;This dissertation addresses these challenges by developing: (i) FDA-regulated medical scanner service fault knowledge development framework; (ii) approach for measurement of knowledge value; (iii) practical modeling to map engineering specification to scanner service knowledge requirements; and (iv) validation and verification framework for the developed knowledge.;First, a model reflecting the current practice for developing regulated knowledge, based upon qualitative input and tools, is adapted to use quantitative input and tools.;Second, an approach is proposed to measure scanner fault service knowledge value as defined by a quantitative improvement in service delivery.;Third, a method is proposed to generate technical specifications from the measure using the quantitative tools described earlier.;Fourth, a testing framework for validation and verification of the developed scanner service knowledge is proposed. This framework uses Monte Carlo simulation, statistical hypothesis testing, service records, and scanner monitoring data to predict and determine the value of scanner service knowledge. This testing framework is combined with modeling, measurement, and design controls to define the "Automated Scanner Fault Detection" (ASFD) methodology.;The proposed ASFD methodology was tested for implementation value and regulatory compliance with industrial case studies of CT scanner faults. The developed fault service knowledge resulted in reductions of 82% in scanner downtime and 51% in applied service time.;The observed advantages of the ASFD method include prediction of changes in downtime and applied service time, identification and correction of sources of error in scanner monitoring data, and efficient development costs. It is proposed that the framework be extended to other manufactured goods.