Purpose: A vast proportion of global megaprojects have not performed up to the expectations of their stakeholders. A failed megaproject has the potential even to derail the economy of a country where it was implemented. Stakeholders must, therefore, ensure that they do not invest in megaprojects that are bound to fail. But, how can stakeholders consistently identify such megaprojects? This paper develops a framework for a metric that can help stakeholders measure the readiness of a megaproject.Design/methodology/approach: A comprehensive literature review identified 19 critical success factors of megaprojects. These success factors were integrated into a fuzzy-based model to develop the megaproject readiness metric. An assessment team studied the levels of presence and importance of these success factors in a candidate megaproject to derive its readiness.Findings: The readiness-based model provides stakeholders valuable insights into the strong and weak areas of a megaproject. It can help stakeholders prioritize and systematically eliminate the identified weaknesses and improve megaproject readiness. While the model was tested on a metro rail megaproject, it can be used on any megaproject across domains.Originality/value: This paper adopts the concept of readiness for the domain of megaprojects. Besides the readiness measurement framework, a vital contribution of this research is its application to a real-life case. Future research can include more granular success factors to improve the estimate of megaproject readiness.

Purpose: Maintenance organizations continue to be under pressure to systematically eliminate maintenance wastes and deliver services that their customers value. To this end, maintenance managers are implementing lean maintenance practices. But how does one consistently estimate the leanness of these practices in their organization? The purpose of this paper is to develop a framework for a metrics – referred to as the lean maintenance index (LMI) that can help managers estimate the leanness of maintenance practices.Design/methodology/approach: Based on a comprehensive review of literature in the domain, this study identifies four factors and nineteen subfactors that are essential for the success of a lean maintenance program. A fuzzy-set-theory-based assessment framework is developed that can be used by an in-house team to measure the degree of implementation of lean maintenance practices in their organization. The authors applied the framework to a maintenance workshop that services diesel engines and other prime movers.Findings: The framework provides maintenance managers valuable insights to help identify the strengths and weaknesses of their organization vis-à-vis their maintenance practices, thus enabling them come up with a firm action plan for future process improvements.Originality/value: This paper adapts the concept of agility and readiness to maintenance work. A key contribution of this study is the identification of factors and subfactors that forms the basis to estimate the leanness of maintenance practices in an organization. Another contribution is its application to a large maintenance workshop that demonstrates the ease of its implementation. Future research in this area can help identify more factors and subfactors and thus improve the estimation of leanness.

This work analyzes the current situation of engineering education in India, especially technical universities characterized by low-quality infrastructure, inflexible curricula, and poor teaching resources including faculty, usually resulting in low student learning and very low graduate placement rates, and identifies the root causes of these problems, summarizes the methodologies adapted by previous researchers in the lean area, and applies the lean manufacturing philosophy to engineering education. This paper applies a value stream map to analyze the current state of engineering education. This technique identifies eight wastes and is given in form of a current state diagram. A future state diagram is presented that recommends solutions to eliminate these wastes. These recommendations make learning processes responsive to needs and provide long-lasting value to students. Overall, it is beneficial in developing a policy for engineering education.