The main aim of the research work presented in this thesis, is the development of anovel framework with the capability of assessing the impact of implementing leanmanufacturing within small-to-medium sized manufacturing firms (SMEs). By assessingthe impact of lean implementation, SMEs can make informed decisions on the viabilityof lean adoption at the conceptual implementation stage. Companies are also abledetermine their status in terms of lean manufacturing affordability.Thus, in order to achieve the above-stated aim, the following were the main set researchobjectives; (1) identifying the key drivers for implementing lean manufacturing withinSMEs, (2) investigating the operational activities of SMEs in order to understand theirmanufacturing issues, (3) exploring the current level of lean manufacturing usage withinSMEs so as to categorise users based on their levels of involvement, (4) identifyingfactors that determine the assessment of lean manufacturing, (5) developing an impactassessment framework for justifying lean manufacturing within SMEs, (6) developing aknowledge based advisory system and (7) validating the impact assessment frameworkand 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 thisresearch study. This comprises literature review, observation of companies' practicesand personal interview. The data collection process involved ten SMEs that providedconsistent information throughout the research project life. Additionally, visitations tothree large size manufacturing firms were also conducted. Hence, the framework andsystem development process passed through several stages. Firstly, the data werecollected from companies who had successfully implemented lean manufacturing withintheir premise. The second development stage included the analysis and validation of thedataset through company practitioners. An impact assessment framework was thus developed with the aid of regression analysis as a predictive model. However, it wasrealised that there were few correlations between the dataset generated and analysis. Thereasons for this were unclear.,aknowledge based advisory system was adopted toconceptualise, enhance the robustness of the impact assessment framework and addressthe problem of the imprecise data in the impact assessment process.Three major factors of impact assessment were considered in the framework and thesystem development process, namely relative cost of lean implementation, a companylean readiness status and the level of value-added to be achieved (impact/benefits).Three knowledge based advisory sub-systems that consisted of the abovementionedfactors were built. Results obtained from them were then fed into the final system. Thethree sub-systems were validated with the original set of data from companies. Thisenabled the assignment of a number of input variables whose membership functionsaided the definition of the fuzzy expert system language (linguistic variables) used. Thefinal system yielded heuristic rules that enable the postulation of scenarios of leanimplementation. Results were sought and tested on a number of firms based within theUK, for the purposes validation. These also included expert opinions both in academicand industrial settings.A major contribution of the developed system is its ability to aid decision-makingprocesses for lean implementation at the early implementation stage. The visualisationfacility of the developed system is also useful in enabling potential lean users to makeforecasts on the relative cost of lean projects upfront, anticipate lean benefits, and realiseone' degree of lean readiness.