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The case study offers interesting learning possibilities and offers the following learning opportunities to the learner. assess and conduct a macro- and micro-environmental analysis, comprehend the nature of the competitive landscape and how it changes when one looks at a digital-only versus an omnichannel marketplace, examine the product mix and policy of the firm and evaluate how it delivers customer value and analyse the pros and cons of growth strategies available to a firm and arrive at a viable and actionable future business and product strategy.

The short case study presents the story of a young start-up called Country Delight. The firm began operations in 2011 and was the brainchild of Chakradhar Gade and Nitin Kaushal. The direct-to-consumer firm addressed urban consumers’ non-articulated, latent need to get “fresh and uncontaminated” milk to their doorstep. Country Delight delivered farmer-to-consumer fresh cow and buffalo milk and milk products based on a well-designed and efficient value chain where the supply chain was either wholly owned or quality monitored by the firm. The firm began operations in India’s National Capital Region and was spread across 15 metro cities. Slowly, over the years, Gade and Kaushal added more product categories.Country Delight had a subscriber base of around 500,000, and the ambitious duo wanted to double their subscriber base and reach one million subscribers by financial year 2025. The firm was looking at various paths to achieve this number. Should Country Delight expand into new geographies? Or look at adding to the existing product portfolio? Diversification into agritourism, like the Pune-based vineyard – Sula, also looked attractive to build consumer engagement. Would taking the consumer to the farmers from whom they sourced the milk and vegetables contribute additional revenue to Country Delight and their farmer-suppliers? As the firm got ready to raise another round of funding, it needed a well-articulated growth strategy that was exciting and profitable for all stakeholders.

This case study presents the dilemma entrepreneurs face as they look at the next phase of growth. Thus, this case study serves as a learning opportunity for a graduate-level course in management and as a sounding board for those who aspire to enter the start-up space. Though this case study has the potential to illustrate basic concepts such as value chain and macro- and micro-environment analysis, the protagonist’s dilemma and the problem statement make it apt for integrated discussions that are critical in advanced electives in marketing management.

Teaching notes are available for educators only.

CSS 8: Marketing.

The aim of this paper is to review the literature on the prediction of cutting tool life. Tool life is typically estimated by predicting the time to reach the threshold flank wear width. The cutting tool is a crucial component in any machining process, and its failure affects the manufacturing process adversely. The prediction of cutting tool life by considering several factors that affect tool life is crucial to managing quality, cost, availability and waste in machining processes.

This study has undertaken the critical analysis and summarisation of various techniques used in the literature for predicting the life or remaining useful life (RUL) of the cutting tool through monitoring the tool wear, primarily flank wear. The experimental setups that comprise diversified machining processes, including turning, milling, drilling, boring and slotting, are covered in this review.

Cutting tool life is a stochastic variable. Tool failure depends on various factors, including the type and material of the cutting tool, work material, cutting conditions and machine tool. Thus, the life of the cutting tool for a particular experimental setup must be modelled by considering the cutting parameters.

This submission discusses tool life prediction comprehensively, from monitoring tool wear, primarily flank wear, to modelling tool life, and this type of comprehensive review on cutting tool life prediction has not been reported in the literature till now. The future suggestions provided in this review are expected to provide avenues to solve the unexplored challenges in this field.