Manufacturing
Nautical Astrolabe
In the word "astrolabe" - "astro means ‘star’ and "labe" roughly translates as ‘to take’ or 'to find.' An astrolabe designed to calculate the motion of Jupiter and its satellites was invented by Gio Domenico Cassini in 1625.The nautical astrolabe, derived from the astronomical one.
Courtesy – photograph by Evan Bench

Data optimization

With growing importance of scalable systems integration in the ever complicated service delivery environments,….

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Product Quality Maintenance

Analytics today can play a big part to improve product quality not only by reducing the number of defects but by effectively predicting the number of defects expected in a particular batch. Analytics can be used aggressive to create patterns that help better understand the interrelationships between quality of output and the various processes that go in making it happen. Understanding the traceability of a defect to the root cause in a multi dimension environment gives managers better insight to fix the problem in the most cost effective and efficient way.

Asset Performance

Maximising asset utilisation is one of the most important tasks of any management team to ensure that the return on capital employed is the maximum. Asset performance both from a measurement and monitoring point of view is a very important aspect where analytics can be used effectively. Co-relation of asset performance with both internal and external factors is an area where analytics can be used to enhance asset performance.

Asset Maintenance

Improving asset availability is an area that can directly add value to the bottom line of any manufacturing organisation. Asset availability is a function of both planning and maintenance. In many organisations preventive maintenance is followed very rigorously for critical assets to ensure continuity of production. However by using analytics preventive maintenance can be converted to predictive maintenance thus allowing for a high availability of the asset at the same time reducing maintenance costs.

Optimizing Warranty Reserves

All costs directly associated with warranty of a product affect the balance sheet of an organisation in the negative. Analytics can be effectively used to predict the utilisation of warranty reserves based on past data. This can help organisations align the costs in a more effective manner and at the same time not tax the balance sheet. Any reduction in warranty reserves directly frees up cash that can be used by the organisation for higher return on investments.

Production Forecasting

Analytics helps manufacturers to establish reliable production strategies to balance production capacity with market demand to obtain optimized returns on their assets. This helps them maintain reliable and predictable interdependencies between demand and production with clear visibility and control over production. Such effective production forecasting and proactive asset management optimizes operations and enables data driven decisions.

Customer Service Performance

With service gaining the differentiation edge, performance monitoring of the services value chain becomes extremely important. Analytics can be used by organizations to identify patterns in customer service needs in co-relation to different parameters starting right from design to demographics. Customer service analytics can help in directly improving customer experience segregating customers in terms of high and low maintenance and as well provide valuable insights to segment customers for future business opportunities.

Demand Planning

As market dynamics evolve, it is increasingly difficult to manage demand planning. Analytical methods enable enterprises to integrate consumer demand with shipment forecasts, review replenishment strategies across supply chain with informed decisions on consumer behaviour and choices.

Production Management

Analytics help businesses make their core processes as efficient as possible with metrics that is accurate, relevant and actionable enabling enterprises to lower their risk exposure, helping them effectively manage & monitor suppliers, process improvements, resource utilization practices and downtimes. Analytics based operational business intelligence helps them improve costs, quality, flexibility and speed of execution in lean manufacturing environments.