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Manufacturers have faced considerable production difficulties in the years following the Covid-19 pandemic. Disrupted supply chains, changing workforce dynamics, and evolving consumer demands are just a few of the key challenges manufacturers are dealing with, leading many business leaders to look for opportunities to optimize their production efforts.
One of the best ways to identify these optimization opportunities is by analyzing production data to find patterns across the prevailing business landscape. By leveraging these analytics, manufacturers are able to understand the forces that are influencing their operations and draw insights to help guide their continuous improvement efforts.
Therefore, manufacturers are increasingly investing in robust digital solutions to acquire and analyze more data from business operations. With these tools, manufacturers are able to gain more precise insights into their workings, allowing them to optimize processes where necessary for better overall business performance.
In this post, we’ll discuss the importance of manufacturing analytics and how you can leverage digital tools to streamline data collection and draw more meaningful insights from your operations.
What are manufacturing analytics?
Manufacturing data and analytics are often used interchangeably, but are fundamentally different.
Manufacturing businesses produce a tremendous amount of data on a daily, and even hourly basis. However, this data is useless unless businesses have the means to process the information in a way that allows managers and supervisors to draw meaningful insights.
Manufacturing analytics, on the other hand, is the discovery of patterns and trends resulting from the data collected within a manufacturing facility.
Many manufacturers today use various systems to run their operations including MES, ERPs, and similar operations platforms. These systems help collect, store, and communicate the data generated by machines and processes.
In more traditional manufacturing settings, operators and supervisors collect this data manually from each machine and process, often using pen and paper. As a result, decision-makers cannot react quickly to production and market changes, putting the manufacturing business at a disadvantage.
However, due to Industry 4.0, businesses now have various tools to collect and analyze data, including the industrial internet of things (IIoT), edge computing, computer vision, and AI-enabled analytics.
These advanced technologies come together to provide various benefits when manufacturers apply them to their businesses.
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Benefits of analytics in manufacturing
When it comes to driving continuous improvement initiatives, manufacturing analytics must permeate all aspects of production. These analytics provide decision-makers with the insights required to move the business forward and make it more competitive.
The benefits of leveraging manufacturing analytics include:
Reduced machine downtime: One of the ways modern manufacturing businesses leverage analytics is to assess machine performance. This allows supervisors to determine overall equipment effectiveness across their processes.
Manufacturing analytics identify changes in machine operating performance, fostering predictive maintenance by allowing teams to fix equipment before it completely breaks down. This reduces downtime, enabling the production line to continue running on schedule.
Better resource utilization: Manufacturing analytics provide clearer visibility into the production process, showing manufacturers how resources are utilized. Real-time analysis shows production managers where they can deploy more resources to keep the production line moving.
Increased supply chain transparency: Supply chains have grown increasingly difficult to manage, providing several opportunities for inefficiency and waste to take hold. As such, manufacturing businesses must leverage data analysis to identify shortcomings and opportunities for better supply management.
This allows manufacturers to optimize aspects like demand forecasting, inventory management, and price optimization for better business performance.
Reduced overall costs: Applying manufacturing analytics to a production business allows for organization-wide optimization. As discussed earlier, businesses can leverage data analysis to optimize processes before, during, and after production.
As a result, businesses can identify inefficiencies quickly and easily, allowing business leaders to issue corrective action and reduce waste leading to significant cost savings.
Uses for manufacturing analytics
Given the benefits, manufacturers should aim to apply data collection and analysis to every aspect of their business if possible.
Here are some of the most common applications of analytics in a manufacturing environment:
Process automation: In traditional manufacturing settings, many repetitive, data-intensive tasks and workflows are handled manually. However, data analysis can help managers identify opportunities to optimize and automate these processes where appropriate.
When automation becomes impractical, businesses can leverage this data to augment operator workflows, identify processes prone to human error, and develop tools to allow teams to work more efficiently and with fewer mistakes.
Quality management: Manufacturing analytics can track scrap trends to paint a clearer picture regarding product quality. These trends allow managers to identify the sources of quality defects and implement solutions to prevent quality issues from happening in the future.
Customer experience: Manufacturers can leverage business data to identify customer preferences, buying trends, and market dynamics. This allows them to offer bespoke customer experiences, increasing satisfaction and driving business profitability.
To reap the benefits of manufacturing analytics, modern manufacturers must use digital tools. These solutions plug into all aspects of the manufacturing operation, drawing vital data in real time and analyzing it to provide actionable insights.
If you’re interested in learning how you can use Tulip to collect data from the people, machines, and processes across your operations, reach out to a member of our team today!
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