Due to the competitive nature of the global economy, organisations are continuously seeking ways of cutting costs and increasing efficiency to gain a competitive advantage. Field service organisations that offer after sales support seek to gain a competitive advantage through downtime minimisation. Downtime is the time between service requests made by a customer or triggered by equipment failure and the completion of the service to rectify the problem by the field service team. Researchers have identified downtime as one of the key performance indicators for field service organisations. The lack of real-time access to information and inaccuracy of information are factors which contribute to the poor management of downtime. Various technology advancements have been adopted to address some of the challenges faced by field service organisations through automation. The emergence of an Internet of Things (IoT), has brought new enhancement possibilities to various industries, for instance, the manufacturing industry. The main research question that this study aims to address is “How can an Internet of Things be used to optimise field service automation?” The main research objective was to develop and evaluate a model for the optimisation of field services using an IoT’s features and technologies. The model aims at addressing challenges associated with the inaccuracy or/and lack of real-time access to information during downtime. The model developed is the theoretical artefact of the research methodology used in this study which is the Design Science Research Methodology (DSRM). The DSRM activities were adopted to fulfil the research objectives of this research. A literature review in the field services domain was conducted to establish the problems faced by field service organisations. Several interviews were held to verify the problems of FSM identified in literature and some potential solutions. During the design and development activity of the DSRM methodology, an IoT model for FSA was designed. The model consists of:The Four Layered Architecture; The Three Phase Data Flow Process; and Definition and descriptions of IoT-based elements and functions. The model was then used to drive the design, development, and evaluation of “proof of concept” prototype, the KapCha prototype. KapCha enables the optimisation of FSA using IoT techniques and features. The implementation of a sub-component of the KapCha system, in fulfilment of the research. The implementation of KapCha was applied to the context of a smart lighting environment in the case study. A two-phase evaluation was conducted to review both the theoretical model and the KapCha prototype. The model and KapCha prototype were evaluated using the Technical and Risk efficacy evaluation strategy from the Framework for Evaluation of Design Science (FEDS). The Technical Risk and Efficacy strategy made use of formative, artificial-summative and summative-naturalistic methods of evaluation. An artificial-summative evaluation was used to evaluate the design of the model. Iterative formative evaluations were conducted during the development of the KapCha. KapCha was then placed in a real-environment conditions and a summative-naturalistic evaluation was conducted. The summative-naturalistic evaluation was used to determine the performance of KapCha under real-world conditions to evaluate the extent it addresses FSA problems identified such as real-time communication and automated fault detection.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:nmmu/vital:28698 |
| Date | January 2017 |
| Creators | Kapeso, Mando Mulabita |
| Publisher | Nelson Mandela Metropolitan University, Faculty of Science |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis, Masters, MCom |
| Format | xv, 197 leaves, pdf |
| Rights | Nelson Mandela Metropolitan University |
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