Abstract:
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.