An automobile manufacturer wishes to predict the failure probability of its cars at a sub-system level. Accurate failure probability prediction would allow the manufacturer to offer appropriate warranty periods to its customers and would also allow it to maintain its warranty reserves at optimal levels. Using a combination of parametric and non-parametric survival models, an automated rules engine is built to predict the failure probability of the different sub-systems and causal car parts. In addition, examination of the failure rates before & after engineering changes allows the manufacturer to measure the impact of such engineering changes on failure rates.
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One of India’s biggest manufacturing houses wanted to institute a mechanism to monitor the performance of its 3-year old dealer loyalty programme. Key objectives included evaluation of the impact of the loyalty programme on sales, and measurement of the engagement levels of the dealers. Circumventing challenges caused by unavailability of sanitized structured data, an integrated visual analytics solution was designed & developed to enable business end users to monitor various facets of the manufacturer’s dealer loyalty programme. With a set of high-end statistical analysis powered dashboards in place, the client was able to analyse the effect of the loyalty programme on sales, measure engagement levels of dealers, uncover operational glitches, etc.
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A manufacturer, facing challenges in managing raw-material inventory levels, wants to put in place a robust inventory optimization solution that helps in controlling costs and ensures uninterrupted production cycles. Forecasting techniques are deployed to project raw-material requirements for the various product lines and related SKUs. The interplay of inventory order costs and storage costs is examined to arrive at optimal inventory holding levels. Supplier data is analysed to estimate appropriate safety-stock levels for the different raw-materials. The result is a robust inventory management system that enables the manufacturer to optimize inventory levels, leading to efficient working-capital management as well as disruption-free production cycles.
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A manufacturer wants to institute mechanisms by which it can boost productivity levels of its operations in a sustainable fashion. A range of linear & non-linear optimization techniques are deployed to model various complexities in the firm’s production cycles. Such models enable the manufacturer to accommodate the 3-way constraints related to time, costs and quality. This allows the firm to put in place business strategies that ensure optimal usage of machinery, materials and people, in order to enhance productivity levels in a sustainable fashion, leading to better capacity utilization and better profitability.
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A manufacturer, facing delays & interruptions in its production cycles, wants to identify & address the underlying reasons for such disruptions. Root Cause Analysis uncovers the principal reasons for production-line stoppages. A range of mathematical & statistical models are deployed to provide solutions to the different challenges, such as preventive maintenance to reduce equipment breakdowns, buffer stocks for raw materials to minimize shortages, and optimal re-ordering processes for raw materials. With such solutions in place, the manufacturer is able to achieve a disruption-free production process, ensuring optimal capacity utilization and better profitability.
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