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Purpose The purpose of this paper is to identify the non-value-adding activities (NVAs) of core making process and to eliminate them through the standardization-of-work (SW) procedures in a manufacturing company. Design/methodology/approach The action-research methodology was adopted for the current study. First, various lean tools were identified through literature review, and the bottleneck area was identified in discussion with the shop-floor executives. NVAs were recorded after a continuous process study including method study and motion analysis followed by the standard operating procedure. Second, the standardized work combination tables were prepared and NVAs were eliminated using the SW procedures. SW has been opted because it is a set of actions which helps in analyzing, improving and controlling the process and it leads to continual improvement. Findings The production logbook revealed that the capacity in this particular workstation was 54 pieces per 7 h work shift against the current production of approx. 45–50 pieces (past data). SW saved 31.6 s per cycle which boosted the production up to 58 pieces per 7 h work shift. Finally, the authors came to know that the productivity of this particular process increased up to 6.5 percent which may upsurge if this action is executed continually with the support from shop-floor executives and management. These results were also compared with previous research works in this area and found significant relevance, and hence, the results appear to be reliable. Research limitations/implications This is a unique study in itself which explores the lean model by assessing NVAs of core making process. The proposed approach needs to be tested across different other core making processes of the case company so as to generalize the effectiveness of SW as well as the results obtained in the current study. Practical implications The current study illustrates an important step to give more visibility to the lean concept by addressing the problem of lack of standard procedures. This study will help the shop-floor executives and managers to focus their efforts in achieving high performance through effective implementation of SW. The study should be of the interest of researchers in the area of lean manufacturing, operations management, productivity analysis, etc. Originality/value The findings of this study are based on the problem formulation for productivity gains using SW procedures in the case company. The study introduces a new perspective for the execution of SW for core making processes. SW created transparency in workflow, enhanced the safety and eliminated the 3Ms. The outcome of the current study was discussed with the production team and management of the company to validate the productivity gains and received an optimistic response. Most importantly, these improvements were achieved with no investment in machinery or tooling.

Purpose The purpose of this paper is to explore the key performance indicators (PIs) that serve as a decision support tool in case of dairy supply chain practices and to analyze their interactions in the context of Indian dairy industry sector. A total of 11 PIs have been identified through the literature review and the opinions of an expert team consisting of managerial and technical experts from dairy industry and academics. Design/methodology/approach A solution methodology based on the interpretive structure modeling (ISM) technique is used to analyze the interactions among PIs and to propose a structural model. The developed model not only helps in understanding the contextual relationship among the PIs, but also in determining their interdependence to assess the supply chain performance in dairy industry. Further, the importance of PIs has been determined based on their driving and dependence power by using MICMAC analysis. Findings The ISM-based model suggests four PIs at first level, three PIs at second level, one PI at third level as well as one PI at fourth level and two PIs at fifth level. Model allocates to the effective information technology, brand management, responsiveness in shipment and accuracy and a control over wastages as the key PIs in the dairy industry sector. The effective traceability systems, cold chain infrastructure, quality management and the support for technological innovations are the next major PIs. There exists no autonomous PI in MICMAC analysis which proves the importance of identified PIs in the case study. Research limitations/implications The proposed model is an attempt to capture the dynamics of milk processing sector and to incorporate all relevant constraints related to internal and external environments that would significantly improve the supply chain performance in the dairy industry. Practical implications The model developed in this study has been tested in the cooperative milk processing units based in India and also discussed with the experts from academics. This work may help practitioners, regulators and dairy industry professionals to focus their efforts toward achieving high performance by the effective implementation of the identified PIs. Originality/value In this study, 11 PIs are considered. Interactions among PIs are evaluated with the help of the ISM matrix. Out of the 11 PIs, six demonstrate both strong driving and dependence power as explained in the MICMAC analysis.

Purpose -The purpose of this paper is to develop a method to select the best alternative in a multi-criteria decision making (MCDM) environment when the decision is taken by a group of members in an uncertain environment. Design/methodology/approach -In this paper, Fuzzy Preference Ranking Organization Method for Enrichment Evaluations (Fuzzy PROMETHEE) technique has been used for MCDM problems. The team of decision makers is constituted to integrate their opinion. The analysis is done using Geometrical Analysis for Interactive Aid (GAIA) plane, available in Decision Lab 2000 software, which provides valuable help in understanding the conflicts among criteria. Findings -The selection of best alternative is done on the basis of generally conflicting criteria. Fuzzy PROMETHEE technique has been proposed and the same is demonstrated using Decision Lab 2000 software. This software can be used for as many criteria as possible and also in a fuzzy environment, where the crisp data for criteria comparison are not available. It is found that the analysis of the results becomes very easy and effective with this software. A case study is conducted for a cement company to select the logistic service providers (LSPs) to demonstrate its ease and effectiveness of use. Originality/value -The research provides a model to choose the best alternative using Decision Lab 2000 software for Fuzzy PROMETHEE technique. The proposed methodology can be used in a fuzzy environment with ease and effectiveness. In the competitive scenario, this could help the industry in prompt and efficient decision making in MCDM problems.

PurposePresented work gives comparative review of food supply chain (FSC) under various notions related to its conceptualisation, operationality and technological advancements in lieu with Industry 4.0 revolution. In Indian scenario, the impression of FSC seems in a scattered way that cannot be directly useful for an organisation, to overcome this scattering, a framework has been developed to consolidate the previous research works and exploration of new trends in food supply chain management (FSCM) in context to Indian scenario.Design/methodology/approachThis article encapsulates the essence of various research articles and reports retrieved from databases of Emerald and Elsevier's Science direct, clustering the various notions related to FSC in Indian context. To visualise the one-sight view of related works, a pictorial representations have also been appended.FindingsThis article explains the general aspect of FSC and its linkage in context to Indian system. Presented work outlays both empirical and theoretical approaches trending from last 15 years. As research count in context to Indian FSC is lacking, so this work will be a road map for expedition in direction of FSCM, in era of research.Practical implicationsFindings and suggestion in this work can expanded in various industries related to food, helping to turn their fortune and enrichment of Indian FSC.Social implicationsFood is binding word for all the commodities, and its effective supply chain management is a big boon for economy of country along with large employment generation for people directly/indirectly associated with this industry. This article covers a generalise approach from ground level framework to a level of advancement which fulfil technological aspects, future needs and upcoming trends in lieu to need of developing nation.Originality/valueAs limited research is done in Indian FSCM, this work to bridge this gap along with a well-defined framework which going to explore FSC. This work is going to be facilitation for researchers of this area as no major review for Indian context has not been published.