Browsing by Author "Achanga, Pius Coxwell"

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    Development of an impact assessment framework for lean manufacturing within SMEs
    (Cranfield University, 2007-10) Achanga, Pius Coxwell; Shehab, Essam; Roy, Rajkumar
    The main aim of the research work presented in this thesis, is the development of a novel framework with the capability of assessing the impact of implementing lean manufacturing within small-to-medium sized manufacturing firms (SMEs). By assessing the impact of lean implementation, SMEs can make informed decisions on the viability of lean adoption at the conceptual implementation stage. Companies are also able determine their status in terms of lean manufacturing affordability. Thus, in order to achieve the above-stated aim, the following were the main set research objectives; (1) identifying the key drivers for implementing lean manufacturing within SMEs, (2) investigating the operational activities of SMEs in order to understand their manufacturing issues, (3) exploring the current level of lean manufacturing usage within SMEs so as to categorise users based on their levels of involvement, (4) identifying factors that determine the assessment of lean manufacturing, (5) developing an impact assessment framework for justifying lean manufacturing within SMEs, (6) developing a knowledge based advisory system and (7) validating the impact assessment framework and the developed knowledge based advisory system through real-life case studies, workshops, and expert opinions. A combination of research methodology approaches have been employed in this research study. This comprises literature review, observation of companies' practices and personal interview. The data collection process involved ten SMEs that provided consistent information throughout the research project life. Additionally, visitations to three large size manufacturing firms were also conducted. Hence, the framework and system development process passed through several stages. Firstly, the data were collected from companies who had successfully implemented lean manufacturing within their premise. The second development stage included the analysis and validation of the dataset through company practitioners. An impact assessment framework was thus developed with the aid of regression analysis as a predictive model. However, it was realised that there were few correlations between the dataset generated and analysis. The reasons for this were unclear. ,a knowledge based advisory system was adopted to conceptualise, enhance the robustness of the impact assessment framework and address the problem of the imprecise data in the impact assessment process. Three major factors of impact assessment were considered in the framework and the system development process, namely relative cost of lean implementation, a company lean readiness status and the level of value-added to be achieved (impact/benefits). Three knowledge based advisory sub-systems that consisted of the abovementioned factors were built. Results obtained from them were then fed into the final system. The three sub-systems were validated with the original set of data from companies. This enabled the assignment of a number of input variables whose membership functions aided the definition of the fuzzy expert system language (linguistic variables) used. The final system yielded heuristic rules that enable the postulation of scenarios of lean implementation. Results were sought and tested on a number of firms based within the UK, for the purposes validation. These also included expert opinions both in academic and industrial settings. A major contribution of the developed system is its ability to aid decision-making processes for lean implementation at the early implementation stage. The visualisation facility of the developed system is also useful in enabling potential lean users to make forecasts on the relative cost of lean projects upfront, anticipate lean benefits, and realise one' degree of lean readiness.
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    ItemOpen Access
    A Fuzzy-Logic advisory system for lean manufacturing within SMEs
    (Taylor & Francis, 2012-09-30T00:00:00Z) Achanga, Pius Coxwell; Shehab, Essam; Roy, Rajkumar; Nelder, Geoff
    This research paper presents the development of a fuzzy-logic advisory system to assist small-medium size companies (SMEs) as a decision support tool for implementing lean manufacturing. The system is developed using fuzzy logic rules, with a combination of research methodology approaches employed in the research study that included data collection from ten manufacturing SMEs through documentation analysis, observation of companies' practices and semi-structured interviews. The overall system comprises three fuzzy-logic advisory sub-systems that feed into a main system. These outputs are relative cost of lean implementation, a company lean readiness status and the level of value-add to be achieved (impact/benefits). The three sub-systems were validated with hard data that enabled the assignment of a number of input variables whose membership functions aided the definition of the linguistic variables used. The main system yielded heuristic rules that enable the postulation of scenarios of lean implementation (Do-it, Probably do-it, Possibly do-it and Do not do-it). This was also validated with a number of firms based within the UK. Moreover, expert opinions encompassed those in both academic and industrial settings. The developed system has the capability to assess the impact of implementing lean manufacturing within small-to-medium sized manufacturers. Hence, a major contribution of the developed system is its provision of the heuristic rules that aid decision-making process for lean implementation at the early implementation stage. The visualisation facility of the developed system is also a useful tool in enabling potential lean users to forecast the relative cost of the lean project upfront, anticipate lean benefits, and realise the degree of lean readiness.
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    Lean manufacturing for SMEs: Enabling rapid response to demand changes
    (2005-12-31T00:00:00Z) Achanga, Pius Coxwell; Shehab, Essam; Roy, Rajkumar; Nelder, Geoff; Lewis, S. W.
    Small-to-medium-sized manufacturing enterprises (SMEs) make significant contributions to most national economies. In the UK for instance, SMEs account for up to 40% of gross domestic product (GDP) and 85% of newly created jobs. However, the current economic turnaround, fostered by recent technological advances in terms of e-commerce coupled with the advent of globalisation, has been felt in the manufacturing sector in general but more severely by SMEs. This paper aims to demonstrate through a case study approach how lean manufacturing can enable organisations to respond rapidly to sudden changes in customer demand.