{"id":226946,"date":"2023-01-31T10:06:35","date_gmt":"2023-01-31T15:06:35","guid":{"rendered":"https:\/\/www.sightline.com\/?p=226946"},"modified":"2025-05-01T15:49:37","modified_gmt":"2025-05-01T19:49:37","slug":"importance-of-predictive-analytics-in-manufacturing","status":"publish","type":"post","link":"https:\/\/www.sightline.com\/br\/importance-of-predictive-analytics-in-manufacturing\/blogs\/","title":{"rendered":"Os benef\u00edcios da an\u00e1lise preditiva para a manufatura: Maximizando o sucesso nas opera\u00e7\u00f5es"},"content":{"rendered":"\n
\"A<\/figure>\n\n\n\n

There is no successful manufacturing facility in existence that runs without data. Without accurate, measurable, and meaningful data optimized through predictive analytics, plants lose their competitive edge as well as dollars on inefficiencies, wasted products, and unoptimized productivity.<\/p>\n\n\n\n

It\u2019s vital that all manufacturing operations from food & beverage<\/a> and consumer goods to packaging<\/a> and textile invest in data and artificial intelligence software<\/a> that ramps up productivity without sacrificing quality\u2014meeting consumer demands and expectations.<\/p>\n\n\n\n

Data is the lifeblood of your operations. You have access to untapped information 24\/7. Are you entirely confident that you\u2019re getting the most out of your data collection processes and that your data is accurately forecasting outcomes to benefit your plant?<\/p>\n\n\n

\n
\"What-Industries-Can-Benefit-from-an-AI-Powered-Data-Monitoring-Analytics-Solution\"<\/a><\/figure>\n<\/div>\n\n\n

Stop Operating in the Past and Look Toward the Future<\/strong><\/strong><\/h2>\n\n\n\n

Only a few short years ago, nearly half of all manufacturing companies<\/a> were still using spreadsheets and manual data entry to monitor their plant\u2019s performance.<\/p>\n\n\n\n

This \u201ctraditional\u201d, manual collecting procedure, however, comes with a slew of problems. Not only is the process tedious, but it is also extremely error-prone and inaccurate. <\/p>\n\n\n\n

When using data to drive your decision-making, you need to ensure your data analysts are working with accurate data to begin with.<\/a>While IoT devices, sensors, and IIoT<\/a> are making the data collection process easier, analysts still need a system to gather, process, and make sense of that data<\/a> in real-time. Not only will the right machine and operations monitoring and predictive software make it easier for analysts to better report happenings to supervisors, but it will also allow workers to make faster and smart decisions on the plant floor. It\u2019s impossible to rely on manual data collection to allow for this to happen, let alone be able to predict future outcomes and production rates efficiently and effectively.<\/p>\n\n\n\n

Benefits of Using Predictive Analytics in Manufacturing<\/strong><\/h2>\n\n\n\n

What is Predictive Analytics?<\/strong><\/h4>\n\n\n\n

Predictive analytics is a type of data analysis that uses statistical models and machine learning techniques to identify patterns in data and make predictions about future events or outcomes. In layman\u2019s terms: predictive analytics collects a ton of data from past and current events and predicts what will happen in the future based on these occurrences.<\/p>\n\n\n\n

After all, history is bound to repeat itself.<\/p>\n\n\n\n

Predictive analytics is an effective tool for businesses that want to understand their data better and use that insight to make informed decisions and improve their operations. Businesses use predictive analytics to forecast trends in data,<\/a> such as sales trends or changes in customer behavior. For example, a company might use predictive analytics to forecast product demand and adjust production accordingly or identify potential supply chain risks and develop strategies to mitigate them. While predictive analytics has been applied in various industries<\/a>, it\u2019s absolutely essential in manufacturing.<\/p>\n\n\n\n

Predictive Analytics Use Cases<\/strong><\/h3>\n\n\n\n

The connected devices throughout your manufacturing facility are collecting data points that allow your analysts and your data collection software to predict numerous occurrences throughout your operations like:<\/p>\n\n\n\n

Reducing Downtime, Machine Failures, and Maintenance Needs<\/strong><\/h4>\n\n\n\n

Managers can more easily plan for maintenance prior to machine failure by using predictive maintenance. What is key here is that predictive analytics allows managers and supervisors to make necessary adjustments when maintenance is actually needed\u2014not just assumed it is needed.<\/p>\n\n\n\n

Because many of the machines at this whole grain manufacturer<\/a> had sealed parts and components, it was difficult to know when routine maintenance needed to be done. All documentation on repairs and usage by maintenance and operations was previously handwritten and filed. When the maintenance team wanted to review the notes, they were often illegible or missing.<\/p>\n\n\n\n

Additionally, after reporting machine problems to maintenance, operators often vacated their area and had no insight as to when maintenance arrived and how long it took to fix the machine, resulting in delays resuming production. This also caused intercompany billing between the departments to be challenged and typically resulted in maintenance being over budget.<\/p>\n\n\n\n

Sightline EDM was deployed and alerted operators when machine processing indicators deviated from expected values so that anomalies can be detected and tracked back to their root cause. This fast and convenient way to identify potential issues increased plant availability and efficiency resulting in almost $100,000 of saving on one line in the first year.<\/p>\n\n\n\n

Quality Control and Reduction of Defects<\/strong><\/h4>\n\n\n\n

Predictive analytics allows managers the invaluable ability to stop or adjust processes earlier to reduce or eliminate waste. Facility operators can use predictive analytics to improve quality control by identifying patterns in data that may indicate potential defects or issues with the manufacturing process. They can also use manufacturing data collection software to analyze quality control data from connected devices and sensors in the manufacturing process. By proactively addressing these issues, companies can improve the overall quality of their products. <\/p>\n\n\n\n

One of our customers\u2014a corrugated packaging company in New Jersey<\/a> with a full-line corrugator operation\u2014had a manual experimentation process where they changed moisture levels, temperatures, pressure, and adhesive mix through their manual data collection, resulting in even more waste.<\/p>\n\n\n\n

With the Sightline\u2019s EDM\u2122 solution in their business optimization arsenal, this client was empowered with the tools they needed to find the most efficient combination of adhesive disbursement and speed to see the substantial results they were looking for,  realizing an instant savings of 11% to their bottom line and a 14% increase in overall product output.<\/p>\n\n\n

\n
\"iiot-case-study\"<\/a><\/figure>\n<\/div>\n\n\n

How Can Predictive Analytics Be Implemented in Your Manufacturing Facility?<\/strong><\/strong><\/h2>\n\n\n\n

Manufacturing operators must balance competing priorities and challenges to operate efficiently and effectively. Implementing predictive analytics in a manufacturing facility can help facilitate this goal and can be accomplished in several ways, including:<\/p>\n\n\n\n