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How Analytics is Automating Manufacturing Processes

By Enterprise Technology Review | Friday, November 15, 2019

Analytics applications can use vast unstructured data from different development phases to allow manufacturers to modernize their operations.

FERMONT, CA: As with any other industry, manufacturing has its own set of challenges. The primary concern for all types of manufacturing units is to increase the yield while maintaining the quality of the products. Manufacturing practices can benefit enormously from tech advancements with technological innovations affecting industries worldwide. With different types of data flooding across multiple manufacturing stages, advanced analytics solutions can provide manufacturers with greater insights. Within the manufacturing processes, companies have large unstructured data sets that can be accessed, structured modeled, and used to make better manufacturing decisions. Here are the key ways analytics can automate manufacturing processes.

Convert Raw Materials into Finished Products

The time required to convert raw materials into finished products is considered as manufacturing cycle time. Different factors such as the manufacturing industry segment, the location of the industry, the scale of the manufacturing operation, and the steady growth of supply chain supporting operations influence the cycle time. The manufacturing cycle involves several redundant tasks that can be automated to achieve better results. Advanced analytics will provide a detailed understanding of the processes, allowing a faster process flow with a significant time reduction required to convert a customer order into a finished product.

Meet the Quality Standards

An extremely important aspect is the inspection of the suppliers' raw materials that arrive at the facility to ensure that the items meet the quality standards. The purchasing department usually negotiates with the supplier to ensure timely receipt of the best-priced products. While ensuring inbound quality levels is essential, a business dealing with a variety of products can be a challenging task. The effective inspection would, therefore, allow companies to have effective analytics with different parameters covering the different quality aspects of suppliers' raw materials.

Achieve Higher Perfect Order Levels

Perfect order performance is a measure of a manufacturer's effectiveness in delivering accurate and undamaged orders to customers on time. Perfect order performance involves different transactional metrics that represent the effectiveness of the performance of fulfillment. Perfect order includes on-time delivery, complete delivery, and correct invoices. Companies are deploying analytics solutions to capture all the metrics through a single platform. Higher analytics and real-time integration can enable manufacturers dealing with complex order fulfillment processes to achieve higher perfect order levels.

In addition to the above, there are other analytics solutions use cases that can optimize the overall manufacturing processes along with improved levels of productivity. There is no doubt that future technological innovations will drive analytics to capture the finer details involved in manufacturing.  

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