How manufacturers can unlock new value from existing data

In an industry buffeted by constant pressure on margins, shifting trade patterns, and supply chain uncertainty, manufacturing companies are looking for any edge they can get. The good news? It can often be found in innovative uses of data.

Here’s how manufacturers can harness data analytics to improve performance across three critical areas of their businesses.

Factories generate enormous amounts of data from sensors, controllers, and other assembly line equipment – but that data is typically thrown away or readily available if it doesn’t indicate an immediate problem. When combined and analyzed over time, however, it can be a treasure trove of operational savings.

Predictive or condition-based maintenance uses historical data about equipment performance to predict the likelihood of future failures. Downtime costs manufacturers billions of dollars per year, yet recent studies have found that many companies don’t have formal systems for tracking equipment maintenance or replacement schedules.

Predictive maintenance saves money in two ways:

• It uses sensor data to monitor for conditions that indicate that equipment is going to fail, such as excessive vibration or heat.
• Analytics can also look across past or similar situations to pinpoint when equipment is in perfect health and doesn’t need scheduled maintenance.

Top-tier automotive supplier Faurecia built an enterprise data hub to bring together data from thousands of machines and millions of sensors to enable it to perform predictive maintenance and improve product quality. The company can now spot quality issues early, reduce unnecessary labor and material costs, and improve customer satisfaction. What’s more, data analytics is moving Faurecia closer to its goal of zero defects.

“If you’re a logistics company, the last thing you want is to have delivery vehicles go out of commission,” said Cindy Maike, Vice President of Business and Product Solutions at Cloudera. “Sensors on vehicles information back to the fleet management group indicating the performance of various component parts to determine either early warning indicators or overall performance.  These signals, along with past service, are used to help avoid downtimes.”

• Enhanced customer engagement

The data a manufacturing company collects about its products in the field can fortify relationships with customers and channel partners. For example, a maker of factory equipment can harvest sensor data to predict failures and alert customers to the need for preventive maintenance. Software updates delivered over the air can save buyers of cars, security cameras, and other smart devices from having to make time-consuming trips to a dealer.

Vodafone Automotive developed an innovative program to help insurance companies tailor policies more precisely. It equips fleet vehicles with a device that collects data about vehicle location, speed, and acceleration. It then translates that information into driver profiles that insurance companies can use to tailor policies and save their customers money. The company’s data fabric has also laid the foundation for real-time services to improve driver safety as well as drive maintenance efficiency for vehicles in the field.

• Improved safety and compliance

Manufacturers in fields like pharmaceuticals and food are keenly aware of the need to keep their customers safe. Quality problems that go undetected can have consequences that not only threaten public health but can incur large regulatory penalties.

“If you’re a pharmaceutical manufacturer, you need to have the right security, governance, and data lineage tracking to take a drug to market,” Maike said. “Everything from R&D to clinical trials to yield optimization needs to be tracked.”

Sensors can be employed to monitor product status and quality throughout the supply chain. For example, a maker of perishable foods can use smart thermometers to ensure that its products are never exposed to unsafe temperatures.

Quest Diagnostics built a big data platform to store the results of more than 20 billion lab tests conducted over the past decade. Quest combines its data with other unstructured and structured sources to derive new clinical insights that improve operational efficiency, enrich clinical reporting, and support the growing need to manage population health and lab utilization.

With the right data management platform, manufacturers can unlock new sources of value. Visit Cloudera to learn more.