How Predictive Analytics Can Help Manufacturing Industry During Covid-19

How Predictive Analytics Can Help Manufacturing Industry During Covid-19
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Understanding the importance of analytics in manufacturing sector.

COVID-19 has had a massive impact on the manufacturing industry. As the industry prepares to revive its operations in these disruptive times, it needs to switch to analytics-driven processes to streamline its operations in the most optimized way.  Let us look at how predictive manufacturing analytics can assist manufacturing industry to get back on its feet, stronger and in lesser time.

Enhance and Maintain Quality 

In the current scenario, the consumer has become extremely quality conscious. Quality checks have become stringent, and with the limited operational permissions, manufacturers need to take all measures possible to highest production quality.  Analytics not only enables manufacturers to improve production quality but also help them to get visibility into leakages and costs associated with poor quality yields. With predictive analytics, manufacturers can enforce quality check and thresholds across multiple production lines and get the best output.

Using machine learning-driven manufacturing analytics, users can quickly analyze a huge volume of data and identify problems even before they occur.

They can get real-time predictions on quality variation across processes and take corrective measures in time. Manufacturers can leverage predictive analytics to foresee warnings and take actions to prevent production loss due to poor quality.

Prevent Downtime with Predictive Maintenance

Downtime due to sudden breakdowns is a major cost factor for manufacturers. It is critical for them to avoid breakdowns and ensure the smooth running of all automated machines.  However, sometimes breakdowns are hard to notice, and subtle changes in temperature or pressure in a machine can lead to massive production downtime.

Predictive analytics helps manufacturers to easily access historical performance of machines, correlate insights and get accurate forecasts on when a machine is likely to suffer a breakdown. Having this information, manufacturers can plan their maintenance cycles in such a way that all anticipated breakdown scenarios are addressed optimally. They can act on the alerts and conduct pre-emptive checks to curb breakdowns.

Manage Demand and Supply Chains

In the current pandemic situation, the demand and supply cycles have been disrupted. Markets are volatile, and the requirement of different products is changing rapidly. This requires manufactures to be on top of their demand, inventory and supply processes and make informed decisions about their production lines to ensure minimum wastage.

With real-time insights on demand and inventory status, manufacturing users can make informed decisions on production quantities instantly. They can visualize historical and current data to determine how much quantity of a product should they produce. Halting the production due to lack of orders can be very expensive for manufacturers. By utilizing analytics, they can easily determine what should be the priority of production line basis the demand trends and ensure that the production is never halted.

In addition, manufacturers can correlate insights to understand the demand fluctuations around special events. They can know beforehand when a product is expected to go on peak or have reduced demand and can plan their manufacturing accordingly with precise intelligence on the quantity to be produced.

Unify Insights from Multiple Devices 

The advent of the Internet of Things (IoT) connected devices and processes has resulted in the creation of huge data piles in manufacturing from multiple systems. Manufacturers can leverage the power of analytics to unify data coming in from disparate data sources and get a centralized view of all KPIs. They can combine data from different PLCs, SCADA systems, ERPs, and other sources, across multiple locations or production units. Advanced analytical capabilities empower manufacturers to interact with their data and dig deeper into a variety of insights through self-serve reports and interactive dashboards.

The need for data analytics with real-time predictive capabilities is at an all-time high in the manufacturing industry. As manufacturers work towards bringing their operations back on track, predictive manufacturing analytics can provide actionable futuristic intelligence and prepare them for the times ahead.

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