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Manufacturing and processing plants might not be at the front of anyone's minds when it comes to tech adoption, but as illustrated by a recent IDC report, The Worldwide Internet of Things Spending Guide, the manufacturing industry is transforming into industry 4.0 and spearheading the adoption of IoT.
Industry 4.0 is the newest industrial revolution, bringing automation, big data and AI into plants and factories around the world. One of the building blocks of industry 4.0 is the internet of things, or IoT. A recent report forecast that spending on IoT platforms would see a 40% CAGR between 2019 and 2024, resulting in spending that exceeds $12.4 billion. In 2019, leading industry corporations were expected to invest almost $200 billion in IoT solutions.
Industry IoT, or IIoT, isn't the only tech field to benefit from industry 4.0. Demand for data integration tools has kept pace, with the two tech fields growing symbiotically. The IDC report highlights trends in industry 4.0 that are driving adoption of IoT and the parallel rise of integrated data.
IoT sensors implanted in myriads of locations create "smart factories" that pump data into control rooms for analysis. These sensors pick up millions of data points every day, reporting on temperature, product quality, balance, air quality, vibrations, and more to track output and report on anomalies in the plant.
Other verticals are keeping an eye on the success of IIoT and following their lead in using devices to track inventory, sales, supply chain, customer demand, and many other data signals to inform better decision-making.
Potentially, manufacturing companies can use IoT data to improve productivity, predict equipment failure, spot trends, improve employee safety and more, but only if they have the right data integration tools to make sense out of the raw data they gather. Otherwise, the data signals pushed out by sensors risk going to waste.
The average plant produces massive amounts of data every day, far more than human analysts can process. Every sensor takes a measurement once every minute, on average, and each factory has thousands of sensors. Each state is sent and recorded in real time, creating an ever-growing mountain of data. Without advanced data integration and processing tools, the firehose of raw data is overwhelming and useless.
Indeed, the data in a plant comes from many different sources and devices. They may use different protocols, collect and store data in different formats, and gather both structured and unstructured data. Non-uniform data can't be aggregated and analyzed by older business intelligence tools, so it risks becoming siloed in outdated data platforms that can't process it, leaving its value to go to waste.
Data can only be analyzed effectively when it's aggregated and integrated into a single data repository. Then it's possible to look for patterns, find actionable insights, and make useful predictions.
When plants make the most of next-generation data integration tools, they can drive revenue and improve their competitive edge in a number of ways. Integrated data from IoT sensors allows plant engineers to spot wear and tear on equipment early, instead of being taken by surprise when a part fails. This enables them to make the proverbial "stitch" in time – an inexpensive fix to a valuable piece of equipment that extends its lifecycle, saves money on replacement parts, and improves RoI on costly items of equipment.
Catching items of equipment before they break also improves productivity by reducing plant downtime while waiting for replacement parts or for long repairs to be carried out. Integrated data from IoT devices helps identify process inefficiencies and assists plant managers to find the golden batch.
Together, IIoT and data integration platforms are creating a connected, digital supply chain that enables industry owners to track the progress of raw materials to the plant, and their finished product to customers. IoT devices in shipping containers send data back to data integration tools so that plant managers can check transportation conditions on a granular level, tracking humidity, vibrations, temperature, and more to make sure that the product arrives undamaged.
Data integration together with IoT also saves lives, for example by preventing collisions that harm plant employees. IoT robots can operate in perilous situations, decreasing the number of human employees who have to put themselves in danger in order to check meters or equipment stability. Advanced data integration tools can analyze millions of states like temperature, air quality, and vibrations, in every area of the plant and each item of equipment. Analysts can then aggregate the data points to spot potentially life-threatening situations before they become critical, and send an alert in real time.
On a general business level, better data and improved data analysis support more informed decision-making, allowing manufacturing enterprises to be proactive rather than reactive and base their choices on data and numbers instead of their gut instinct. Many other verticals are also discovering the benefits of using data integration platforms to analyze customer behavior data, in order to better understand customer needs and predict demand.
Industry 4.0 relies on IoT to provide the data that forms the foundation of better decision-making and greater visibility into the complex environment of plants and factories, but it needs data integration tools to unlock value from that data.
Working together, IoT and data integration platforms can increase productivity, improve RoI, provide visibility into the supply chain, raise plant safety, and inform better business decision-making to help manufacturing and process industry to grow their bottom line. As IoT adoption continues to rise, data integration platforms can expect to see similar gains. The rise of industry 4.0 thus offers new opportunities and revenue potential for data integration platforms.
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