With the increase in the varieties products and the increasing uncertainty about product demand, the production preparation time is a significant factor in addressing these issues. The trade-off between the reduction of the production preparation time and the associated cost remains a critical decision. With this backdrop, this study presents a continuous review production-inventory model with a variable production preparation time and a time-dependent setup cost. The demand during the preparation time is captured through a min-max distribution-free approach. In a stochastic framework, the order quantity, reorder point, and setup time are optimized by minimizing the expected cost considering the time-value effect. Further, a fuzzy model is formulated to tackle the imprecise nature of the production setup time and demand. Two algorithms are developed using an analytical approach to obtain the optimal solution. A numerical illustration is given to present the key insights of the model for effective inventory management. It is observed that order quantity and total cost are more sensitive at the lower side of the optimal setup time rather than at the higher side. The discount rate is also found to be a sensitive factor while minimizing the total expected cost.

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Indian National Food Security Programme, with a goal to provide highly subsidized food grains to more than 800 million people in every nook and corner of the vast country, faces strategic challenges related to production, procurement, storage, transportation, distribution, finance, and organization. While the production issues are related to low yield, small farm size, and lack of financial support, the procurement process is skewed and lacks integration with the markets. The storage facilities are inadequate and are non-optimally located. Transportation facilities lack coordination leading to multiple loading and unloading of the food grains. Leakage and improper distribution of food grains are also big challenges. Very high subsidy, inefficient processes, and a large work force have brought to the fore the question of financial viability of the programme. There are also organizational issues related to payment disparity and resistance to labor reforms. The paper has also given a framework for efficient implementation of the programme using cloud system with effective procurement and stock management policy measures.

This study investigates an economic order quantity model of deteriorating items, where demand is fuzzy in nature and depends on promotional effort with full backorder for a given time horizon. The learning effect in the fuzzy environment is added in this model. A constant deterioration rate is assumed. Under these circumstances, a mathematical model is developed to curtail the total cost over a finite time horizon by determining the replenishment order quantity, number of replenishments, and the fraction of the replenishment cycle when inventory is positive. A solution algorithm is developed to find the optimal solutions. The applicability of the proposed model is illustrated through numerical examples. To get further insights, sensitivity analysis is carried out for the main parameters in crisp, fuzzy, and fuzzy-learning environments.

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PurposeMaintenance 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/approachBased 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.FindingsThe 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/valueThis 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.

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