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Smart Solutions for Smart Machines

Leverage new business models for differentiation.

Powered by smart machines, the new industrial revolution is changing how manufacturers operate today and plan for the future, influencing a significant transformation in manufacturing, engineering and factory-floor industries. Adding to this, manufacturers are under pressure to meet the demand for faster delivery of new products, coupled with shorter production lifecycles. Organizations are adopting agile, flexible production plant systems and processes to adapt and evolve, so as to remain competitive and profitable. Going forward plants and machines will have to be smarter, better connected, more efficient, flexible, and safe.

Over the past several years, innovation frameworks have emerged in industry organizations worldwide, such as Industry 4.0 (Europe), the Industrial Internet Consortium (America), and the Made-in-China initiative, to name a few. The focus of these frameworks is to merge operational technology (OT) with information technology (IT) to better automate and network industrial machines with business systems. This union of IT and OT, coupled with the use of Industrial Internet of Things (IIoT) -enabled solutions, creates new opportunities for organizations.

By utilizing IIoT-based solutions, machines and processes can be continuously monitored and controlled, no matter where in the world they are located. In addition, data can be captured, stored, and analyzed anytime, giving businesses the potential to use insights from smart machines to generate business value for machine builders and users.

However, data collection is just one piece of a broader opportunity as part of the next generation of IIoT. Smart machines that can respond to changing conditions without human interaction, maximize efficiencies, and evolve their levels of intelligence to accommodate predictive planning and flexible business needs can help manufacturers further evolve their business models to meet today’s demands, as well as improve operations, safety, and efficiency.  

As the adoption of smart machines rapidly accelerates, tools such as simulation software, templates, remote monitoring, and Cloud-based analytics will help machine builders better support end user applications and enhance the ability to innovate. New smart machines are using established communication protocols, IIoT devices, and the Cloud to enable life cycle cost reductions and machine performance improvements.

But for companies too small to implement or afford emerging smart machine technologies to reap the benefits of IIoT, new business models can and should be used. While automation business models have remained static, internet connectivity and remote management are enabling market opportunities for new products and service offerings. Examples include equipment leasing and pay-per-use models, which allow companies of all sizes to lease complex machines and have them remotely managed.

Software professionals are increasingly moving away from license-based models that rely on the fact that new functions will be attractive enough to motivate a customer to re-buy a platform. Instead, software-as-a-service (SaaS) models are being offered as a subscription and combined with pricing models that require regular payment or as a pay-per-use basis. With this model, it’s possible for end users to have access to equipment at a lower cost and have maintenance covered by the manufacturer; upgrades could be customized to the company’s business needs.

There are three specific services manufacturers can offer within the emerging leasing and subscription-based models:

Virtualization services. Virtualization eliminates the need of a physical network. Replacing servers and storage resources can increase the value of products for OEMs. Without a doubt, virtualization has greatly increased the ability to utilize and scale computing power.

Code quality management. OEMs today find it difficult to determine whether the code that has been handed over is robust, maintainable, and performing to its peak. It is even more difficult to measure whether code has improved over time. In IT development, for example, there are several standards that are transferring to the operational technology (OT) world. A single item can be difficult to sell at a high price, so a service-based model for code quality management can help to maximize value while simultaneously offering an acceptable pricing model.

Data analytics (partnered with condition and event management services). The most obvious application for analytics in industrial systems is for predictive maintenance, which can be offered as a service by manufacturers. Data analytics can support preventive maintenance, productivity and workflow optimization, and monitoring and event activation. Analytics is one of the factors that makes a machine smart and serves as the base for end-to-end automated decisions. With these capabilities, companies of all sizes can glean the insights needed to improve operational performance and productivity.

The services listed above may provide a gateway for companies to leverage new technologies offered by IIoT to improve performance and efficiency, while reducing downtime and energy consumption. With service-based offerings, both machine builders and end users can differentiate themselves from the competition. Those who fail to take any new action will be left behind in a transitioning marketplace. A significant opportunity for machine builders is the development of new services to support IIoT and smart machine processes. Now it’s up to standardization groups and the automation suppliers to pave the way for OEMs into the new evolving world.

TAGS: Awareness
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