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Advanced big data analytics is a hot topic for the manufacturing industry. Manufacturers are generating vast amounts of data through their systems, but are they using it to optimise overall operations?
First, let’s answer a basic question: What’s the added value of data analysis? It’s all about uncovering critical information to enable smart operations and drive the business. Whether you look at your shop floor, your supply chain or procurement, advanced analytics helps you identify patterns and dependencies within your systems. By doing that you can make right decisions or optimise the whole process. Typical use cases for manufacturing are:
Predictive maintenance: Knowing when a part is going to break reduces downtime and waste. By analysing factors that drive the wear of your devices, you gain transparency on the real lifetime of your products.
Automatic quality testing: Automating this task saves time and helps avoid human errors. Instead of using manual checks, quality can be tested incorporating data from special test devices, X-ray scans, photography, etc.
Product optimisation: Understanding what drives the quality of your production avoids waste and improves the overall equipment effectiveness (OEE). Advanced analytics identifies parameters that cause variable levels of quality or efficiency.
Supply chain optimisation: Anticipating the right time to produce orders or plan shipping dates enables on-time delivery and resolves storage issues. Analysing the duration of individual processes and the complex interdependencies among them provides information about transportation times and the impact of disruptions.
Many more use cases are out there. How manufacturers will benefit from data analysis really depends on their capabilities, the available data and their ideas.
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