Purpose -The aim of this research paper is to present the critical factors that constitute a successful implementation of lean manufacturing within manufacturing SMEs. Design/methodology/approach -A combination of comprehensive literature review and visits to ten SMEs based in the East of the UK were employed in the study. The companies' practices were observed to highlight the degree of lean manufacturing utilisation within these companies. This was followed by interviewing of the relevant and key personnel involved in lean implementation. Results were analysed and validated through workshops, case studies and Delphi techniques. Findings -Several critical factors that determine the success of implementing the concept of lean manufacturing within SMEs are identified. Leadership, management, finance organisational culture and skills and expertise, amongst other factors; are classified as the most pertinent issues critical for the successful adoption of lean manufacturing within SMEs environment. Research limitations/implications -Continued scepticism within SMEs about the benefits of lean to their business is one of the fundamental limitations this research faces. SMEs are, therefore, not very willing to provide useful information and data, timely for further investigation. Originality/value -The novelty of this research project stems from the realisation of critical factors determining a successful implementation of lean manufacturing within SMEs environment. The results would provide SMEs with indicators and guidelines for a successful implementation of lean principles.

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This research paper presents the development of a fuzzy-logic advisory system to assist smallmedium 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 subsystems 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 subsystems 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 doit, 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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Benchmarking can be described as an alliance between partners to share information on practices, processes and measures to stimulate innovative improvement in corporate performance. Small- and medium-sized manufacturing enterprises are reluctant to participate in benchmarking studies due to lack of time, financial and personnel resources, and difficulty in selecting partners. A diagnostic benchmarking process has been developed to meet the requirements of smaller enterprises. The process involves a business needs analysis, which provides participating companies with a fresh perspective on their strengths and weaknesses. The analysis connects to business performance, and is supplemented by a benchmarking study to help the company progress towards best practice excellence.