How big data analytics platforms in manufacturing optimises production

The manufacturing industry has always thrived, thanks to the right technology and tools. 

During the 1800s, the industry thrived due to the development of machinery. Now, as the fourth industrial age takes over, we are seeing the advent of new technology that can boost productivity and remove traditional obstacles preventing the industry from reaching its full potential. 

The main challenge, today, is the absence of a platform that can analyse data and break it down into useful insights that optimise the manufacturing process. Fortunately, big data analytics platforms in manufacturing can optimise your production and cut down on costs.

While I have explored how data analytics can improve manufacturing in the past, in this post, I focus on how we can boost productivity and operating costs.

Optimising manufacturing processes with data analytics

Here are some of the ways big data analytics in manufacturing can add value to your operations.

Manufacturers can ensure quality across batches

While custom manufacturing is a consumer-friendly practice, there are certain industries where consistency in quality is key; for example, pharmaceuticals. In this industry, the product is often made in a series of batch processes, which can lead to inconsistencies in product quality.

By using data analytics, organisations can conduct multivariate data analysis. The intent, here, is to better define quality control parameters and use continuous process verification to ensure consistency in product quality. 

Furthermore, real-time manufacturing analytics can provide manufacturers with the insight they need to reduce batch variability. They can use the information to adjust process parameters during manufacturing to reduce deviations that might compromise product quality.

Manufacturers can predict trends, causes, and effects

Advanced data analytics uses high-level methods to conduct sophisticated multivariate data analysis (MVDA). 

This new level of analysis allows manufacturers to analyse data using several variables at the same time. What this means is that manufacturers can perform “what-if” calculations, allowing them to conjure multiple scenarios. The ability to project the future, based on different variables, can help your company future-proof business strategies and determine where your processes could go wrong. 

This makes it easier to make long-term structural adjustments that optimise production.

Analytics can remove bottlenecks in operational productivity

It’s somewhat common to encounter bottlenecks when it comes to production. These bottlenecks could be a result of poor equipment efficiency because when equipment breaks down, it can halt the entire production line, driving up operating costs. 

By using analytics in manufacturing, you can collect data from different sources, like ERP, the environment, and maintenance. This helps you determine when your equipment requires maintenance and prevent breakdowns during production.

Manufacturers can change input processes to discover new inputs

Advanced analytics in manufacturing can help organisations in the industry make unexpected discoveries through experimentation. For example, by using big data analytics in manufacturing, manufacturers can experiment with different inputs like carbon dioxide, temperature, and coolant pressure. 

This calculated experimentation allows you to make unexpected discoveries in your industry.

Analytics makes product customisation easier to pull off

Big data analytics platforms in manufacturing can make product customisation easier to execute. Customisation in manufacturing is becoming a pivotal part of the industry. But, while it sounds awesome in theory, it is very difficult to pull off in practice. This is because making the shift from mass production to custom production is not possible without the right equipment. 

Data analytics platforms make this a more practical feat. Big data analytics tools give manufacturers the insight they need to analyse the different factors that determine custom manufacturing, like customer preferences and production processes, making it much easier to customise manufacturing.

Removing complexities in the supply chain

In a global, connected environment, supply chains can be long and complex. 

Analytics in manufacturing can help streamline the supply chain, reducing operating costs and optimising production. With this level of insight, it allows manufacturers to examine the ins and outs of the supply chain and pinpoint existing weaknesses. 

Optimising production with big data analytics platforms in manufacturing

Big data analytics platforms in manufacturing help organisations maintain the right balance of production processes and variable inputs to optimise production and reduce operating expenses. 

Manufacturing analytics can help optimise business processes either by reducing the variable inputs needed or by discovering new methods to improve production.