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4 Ways Manufacturing Analytics Can Help Businesses to Optimize Their Operations and Reduce Costs

Sep 5, 2019

Businesses that can constantly discover new ways to streamline their operations are successful in the manufacturing industry. Earlier manufacturing companies used to invest a lot of time and resources to examine every single manufacturing process, testing and re-testing innovative ideas and finally implementing changes. However, with the advent of manufacturing analytics, today businesses are able to improve their manufacturing operations more efficiently. With the help of manufacturing analytics, businesses can easily streamline their operations by gaining actionable insights that can further help them to fine-tune their production line. In this article, we have highlighted four ways in which businesses can make noticeable improvements in their manufacturing operations using manufacturing analytics.

Speak with our analytics experts to learn how you can use smart manufacturing analytics and simulations to analyze your manufacturing operations and cut down costs.

Benefits of Manufacturing Analytics

Production Schedule and Capacity Optimization

When it comes to production scheduling and capacity planning and optimization, most organizations tend to have a hard time. They find it difficult to minimize the discrepancies between their capacity and the demands of their customers. Consequently, most of them are under-utilizing resources or are unable to fulfill customer demand. Manufacturing analytics can help companies in the manufacturing industry to identify, quantify, and prioritize margin improvement opportunities by offering detailed insights into SKU velocity, price band, and segment performance, etc. As a result, manufacturing businesses can improve their production schedule and capacity optimization techniques.

Quantzig’s manufacturing analytics solutions can help you streamline your production processes, improve supply chain efficiency, and increase customer service levels. Request a free proposal to gain in-depth insights into our portfolio of manufacturing analytics solutions.

Packaging Schedule Optimization

Manufacturing companies mostly leave their packaging decisions to designers and marketing experts who know how to market and make the products reach to the target customers. Unfortunately, this takes a lot of time and consumes a lot of resources. Manufacturing analytics can help companies to cut down costs by minimizing the number of switches across the production and bottling lines. It can offer predictive scheduling analysis insights that can help companies to gauge resource availability, and resource utilization capacity to make predictions about future workflows.

Predictive Maintenance and Scheduling

Manufacturing analytics also helps improve production efficiency through predictive maintenance and scheduling. By leveraging advanced data analytics solutions, companies can improve the efficiency of production lines by predicting the number of goods that will pass or fail a quality inspection. Through predictive maintenance and scheduling, companies can precisely identify risks and failures of their assets and can improve their ability to be responsive to the unique pressures on each machine.

Request a free demo now to know how our manufacturing analytics solutions can help you to track all costing activities including resource consumption and final output costing.

Cost to Serve Optimization

Manufacturing analytics solutions that leverage advanced data mining techniques, can help companies to gain valuable insights into the actual cost of supplying a specific product to the customer by modeling all logistics activities in the network. Also, it can help businesses to quantify the value of negotiated service levels, shipment exceptions, and other overhead costs. With a robust manufacturing analytics process, businesses can not only gauge the profitability of products, customers, and routes to market but adopt a data-driven approach to decision-making on product mix, service mix, and operational changes for each customer.

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