The manufacturing industry is evolving at a rapid pace with more and more organizations looking to implement industrial IoT applications. New IIoT applications advancements are significantly expanding the potential use case and solution environment. Organizations are leveraging pre-built IIoT applications from leading companies that have extensive and integrated product offerings. These industry changes make it easier for businesses to focus more on integrations, diversifying offerings, and expanding domain expertise to ensure the success of their business.
PTC’s State of IIoT 2019 report found that 89% of respondents expect to transition their industrial IoT applications to production environments within the next year.
Should You Implement Industrial IoT Applications?
IIoT applications are being deployed across all types of industries, especially manufacturing, to optimize operations. These applications have the potential to improve productivity and efficiency while freeing up resources for strategic product differentiation. They can also be used to address recurring challenges facing the manufacturing industry like downward cost pressures and the growing skills gap.
Companies are focused on finding ways to use IIoT applications in their own factories and the factories of end-users. By using digital twins to improve predictive analytics and reduce downtime, organizations can easily improve productivity. And the use of this technology is quickly expanding. Many traditional “black box” products are looking to benefit from predictive analytics used in IIoT applications:
- Material handling and warehousing systems
- Transit systems
- Power transformers
- MRI machines
- …and more
Manufacturers are increasing their reliance on IIoT applications, advanced analytics, and augmented reality (AR) to improve throughput across their factories and improve customer satisfaction. According to PTC, 38% of their customers have connected products where reducing unnecessary services calls, improving first-time fix rates, and maintaining uptime are now considered core feature requirements.
For IIoT applications to be useful, they must have seamless connectivity with new and existing equipment. Organizations must consider how they are going to modernize their autonomous tools and machines to be integrated into today’s connected environment. Beyond connectivity gaining values from these tools requires a way to manage and contextualize data for actionable insights.
Operational intelligence and predictive maintenance are the main focuses for groups implementing IIoT applications. Operational intelligence and optimization have been long-term concerns for manufacturing organizations. Predictive maintenance is a newer concept that is changing the philosophy of systems which are moving from reactive to proactive systems. Instead of scrambling to deal with problems after the fact, new machine learning algorithms can detect and analyze operational thresholds to alert personnel of upcoming anomalies before they occur. Early intervention significantly reduces risk and supply chain interruptions.
IIoT adoption is a global phenomenon, with adoption currently at 35% in the Americas, 30% in EMEA, and 30% in APAC.
Reducing Operational Costs
Unplanned maintenance and downtime have far-reaching impacts. They cause a ripple effect down the supply chain impacting costs, logistical planning, and customer satisfaction. Integration with critical partners and customers can minimize these impacts by providing earlier insight into potential problems. This insight allows partners and customers to implement alternative plans to reduce negative impacts and preserve productivity.
The IIoT market is expected to grow to more than $1 trillion over the next 3-4 years.
Successful IIoT Deployment
Organizations looking to implement industrial IoT applications should make deployment model and data storage decisions carefully. As more and more projects move outside a factory’s physical location with remote monitoring, on-premise or private cloud solutions may not provide the results you are looking for. Customers must consider their entire technology stack and partner ecosystems before starting an implementation project. They must also revisit their decision regularly as rapid IIoT applications advancements continue and require more demanding solutions.
Most businesses will find that utilizing the cloud option is the best way to handle their IIoT application solutions. Companies should look for solutions that are cloud-native so they can easily utilize the scalability and massive storage capabilities that these solutions provide. The way trends are moving, only technology that can integrate into a cloud environment will be viable as part of a long-term operational stack, so getting ahead on this set up will be beneficial for your organization.
The Value of Implementing an IIoT Application Strategy
The value in implementing an IIoT application strategy is more apparent as organizations are able to increase productivity, decrease operational costs, and get to market faster. These strategies can only be supported by the underlying technology that streamlines integrations and ensures application maintenance simplicity. Organizations should look towards pre-built solutions that include customization capabilities to meet their unique needs.
Implementing an IIoT application strategy will allow organizations to meet market demands and stay at the forefront of innovation.
The drive to implement an industrial IoT application strategy will only continue to increase. As part of the digital transformation, organizations must be ready to handle the increasing market demands to remain competitive. A robust IIoT strategy can be easily implemented with a partner who has technological and industry expertise to execute and deploy your solutions.
If you’re interested in learning more about available IIoT applications and how we can help move your organization forward in the digital transformation, contact us.