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Successful manufacturing depends on businesses constantly finding new ways to streamline their operations

PRODUCTIVITY IMPROVEMENT Five ways Manufacturing Analytics will change business

Dec 14, 2018

Manufacturing dashboards and analytics can streamline operations by giving more focused and actionable insights that help to continuously fine-tune production line. The article informs five ways of using data analytics in manufacturing that can lead to noticeable improvements across operations

Successful manufacturing depends on businesses constantly finding new ways to streamline their operations. In the past, this meant spending months examining every single process, testing and re-testing innovative ideas, and finally implementing changes. However, this outdated mindset can sink manufacturers before they gain the opportunity to make improvements. Nevertheless, there are effective ways by which you can improve manufacturing operations faster and more efficiently.

1. Understand the supply side of your manufacturing chain

Purchasing is a standard part of most companies’ supply chains, but one that can easily be ignored when you’re too busy trying to improve upon other aspects. Starting off from a faulty supplier, or one that is a few cents too expensive per component may not seem like the end of the world, but if you produce thousands of products a day, a cent here or there turns into thousands of dollars on your ledgers.

Manufacturing data analytics can help understand the cost and efficiency of every component in your production life cycle, all the way from your suppliers’ trucks. Advanced analytics can help you reach better decisions by visualising how each aspect impacts the final result. If certain components are constantly failing, or are not doing exactly what they need, analytics will help you spot them before they become an issue.

2. Create systems that can fix themselves

Manufacturing systems are constantly operating under heavy loads, and any stoppage in work can translate to spiraling losses. Even so, the best solution many companies have available for fixing issues is waiting until they happen before resolving them. This reactive system has worked until now, but only because there was a clear lack of better alternatives.

By incorporating Big Data analytics, companies can develop manufacturing systems that can consistently gauge their own need for repairs. This empowers systems to fix themselves in many cases and provide early alerts for situations that are not so easily resolvable. More importantly, Data Analytics can deliver insights into which components fail most frequently, letting you turn your reactive solutions into proactive ones.

3. Better understand your machine utilisation & effectiveness

One of the biggest problems manufacturers run into is wasted time. While manufacturing chains can be built with efficiency in mind, different factors may play a contributing role in reducing the overall efficiency of the line because of poor installation, misuse, or simply a lack of downtime coordination.

By combining existing IoT systems with a powerful predictive analytics manufacturing suite, companies can gain real-time insight into how well their manufacturing lines are operating, both on a micro and macro scale. Understanding how downtime for a single machine can affect the chain, or how different configurations may improve overall efficiency isn’t just a pipe dream, it should be a necessity. Generating actionable data that lets you realise real improvements in the overall process is a major advantage of applying analytics to manufacturing.

4. Create better demand forecasts for products

Every manufacturer knows that they are not just making their products for someone today, but also for the perceived demand that will emerge in the near future. Demand forecasts matter because they guide a production chain and can be the difference between strong sales or a warehouse full of unpurchased inventory. For most companies, forecasts are based on previous years’ historic values, and not on more actionable forward-looking data.

However, manufacturers can combine existing data with predictive analytics to build a more precise projection of what purchasing trends will be. These predictive insights are based not just on previous sales, but on processes and how well lines are operating, leading to smarter risk management and less production waste.

5. Manage your warehouse better

Another sometimes-overlooked aspect of the manufacturing process is storage. Once products are ready to be shipped, they must be placed in warehouses before leaving for their destination. At this point, seconds and minutes become important, especially in a world that is increasingly embracing ‘just-enough’ and zero-inventory models.

Managing warehouses, is more than simply finding space for products to wait. Establishing efficient arrangement structures, better product flow management, and the most effective replenishment procedures can improve operations, as well as bottom line. Advanced analytics make it easier to understand how to improve inventory and manage warehouses better.

Bringing your manufacturing processes into the 21st century can be a straightforward process. By incorporating robust analytics and visualisation tools, one can build a more granular understanding of how production line operates, and how one can streamline it further.

https://www.sisense.com/blog/5-ways-manufacturing-analytics-will-change-your-business/

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  • Manufacturing data analytics can help you understand the cost and efficiency of every component in your production life cycle

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