The discrete manufacturing sector is highly competitive and price sensitive. Factories require every machine, production line and employee to contribute to achieving optimal yields, high operational efficiencies and cost controls. It’s this cut-throat environment that’s behind the industry’s rapid move toward digital transformation, a key component of the fourth industrial revolution (or Industry 4.0). One primary way manufacturers are planning to modernize in this new era is by fully using their data. However, there’s a major roadblock that stands in the way of reaching this milestone. Data sets in industrial settings are so massive and complex that they defy human analysis, forcing businesses to find another way forward. And only 3% of companies admit they’ve got the right tools in place to properly use data to increase operational efficiencies.
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Rather than leave this extraordinary opportunity for business improvement on the factory floor, a growing number of companies are using IIoT products and services to convert their real-time, historical and other systems data into meaningful business knowledge to increase factory output, improve efficiency and stay competitive.
Valuable lessons can be learned from these trail-blazing businesses that have successfully cracked open the data and are on their way to becoming a modern, data-driven business. Here are some key things to consider:
#1 The data dilemma is real
Manufacturing businesses gather an estimated two exabytes of operations data annually. This information comes from sensors built into motors, conveyor systems, 5-axis machines and other physical assets throughout their factories. It also comes from historical operational data sources, in addition to several other related systems, such as line-level programmable logic controllers, human-machine interfaces and enterprise resource planning systems.
The next phase in factory automation is expected to grow these data counts exponentially. In fact, new forms of digital technology, including touch interfaces and augmented reality systems are already popping up in the modern factory.
Considering this current and future data outlook, manufacturing executives must recognize these massive data sets are far too vast for humans to examine. It’s IIoT that’s needed to make timely, smart, data-informed decisions. IIoT’s advanced cloud-based data analytics, machine learning and predictive reasoning helps transform rich operational data into tangible business improvements.
#2 ROI is not far away
Once appropriately analyzed and acted upon, a company’s streaming and stored data become vital business assets, enabling production improvements, cost savings and smarter resource allocation.
For instance, manufacturers can use IIoT-based data analysis to:
- Establish condition-based maintenance schedules to reduce unplanned equipment downtime, better manage servicing costs, optimize production and extend the useful life of equipment;
- Use rules-based automation and remote control access to maximize yield while also maintaining quality, prolonging equipment lifespans and remaining compliant;
- Automate and connect every corner of the factory floor to optimize processes and material flow for more precise planning, just-in-time manufacturing and workplace safety;
- Make machines more autonomous, such as automated guided vehicles and industrial/collaborative robots, to reduce the workload of IT, operations and engineering staff; and
- Find the core determinants of production and workflow performance, then take action to continually improve them.
And these are not the only applications of IIoT that can significantly improve financial outcomes. A PwC survey of industrial sectors, for example, projects that 10% of all companies that digitally transform their factories, and 27% of “first movers” that do so, will simultaneously achieve more than 30% increased revenue.
#3 Precise goals key to success
It’s important to note that manufacturers are not investing blindly in the brave new, digitally transformed world. They are strategic about where they make their investments in order to reap the most reward.
A recent study from Bsquare (registration required) revealed that logistics (95%) — including that on the factory floor — was the most common challenge being tackled by manufacturers that are currently adopting IIoT. The other two top priorities were machine health (82%) and operating costs (34%).
Whatever the goal, IIoT systems have become a factory’s secret weapon to aggregating their full repository of data now and into the future. By unlocking previously unknown operational insights, businesses will be able to increase output, manage costs and improve productivity to secure their inclusion in the prestigious class of Industry 4.0.
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