The manufacturing sector constantly looks for ways to improve productivity and maximize efficiency. That includes automation of the production process, digitization of inventory management and techniques to optimize the potential of each laborer. However, such processes aren’t enough to best the competition, so there’s always continuous efforts to address inefficiencies both within operations and on each end of the supply chain. In many ways, predictive analytics software can play a prominent role in fixing these gaps to make a more effective business. It can both prevent production stoppages from happening on the shop floor and increase supply chain visibility for customers everywhere.

Proactive and preventative measures
The most significant problem internally at a manufacturer is a work stoppage. In recent years, the number of reasons for these interruptions  has shrunk. Most often, issues that occur are equipment failure, misuse or employee mistakes. Some of the ways companies address these problems include preventative maintenance of the equipment and increased automation to cut down the potential of human error.

Predictive analytics takes these roles a step further, according to manufacturing expert Martyn Williams in an article for LinkedIn. He noted that the key to this success is the Internet of Things. Machinery now connects to the Internet to create a smart factory. Now equipment can report their statuses in various different parts. Through trend analysis, companies can figure out what causes a machine to break down and at what point it’s most likely to do so.

Manufacturing can reap the rewards of predictive analytics.
Manufacturing can reap the rewards of predictive analytics.

Analytics’ strong suit of pattern recognition comes into play when establishing relationships between specific tasks and failures. This can help identify the culprits of component breakdowns, establishing schedules to prevent incidents from happening in the first place. As robotics become more common on assembly lines, classifying the risk level caused by degradation will be more difficult due to their sophistication. Predictive analytics can assure a production uptime of close to 100 percent.

Seeing the situation from the customer side
Supply chain visibility is a process that is practically a mantra for manufacturers now. Knowing the situation from the supplier side can help determine costs for materials and necessary parts. Understanding how distribution handles delivery of products can help assess how much to sell completed goods. However, predictive analytics can take things a step further by taking the entire supply chain into perspective and create an image of the development and lifecycle of a certain product to determine faults in production, as reported by IndustryWeek.

Moreover, while customers demand more from manufacturers, they can also supply more information. Predictive analytics can thus paint a complete scenario of a single product created by a company, from the extraction of the raw materials by suppliers to when the completed item finally breaks down for the last time. By analyzing the production lines and methods, scheduling, retools and redesigns, client demographics and overall usage, businesses can determine the viability of their current product line and make adjustments to become more profitable.

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