Improving Service and Profits With Connected Products

How can you deliver better service to your end user customers with more profitable business models? Read More

Equipment as a service: Answering OEM questions (eBook)

Original equipment manufacturers (OEMs) need new ways to grow revenue and differentiate themselves as the state of the industry evolves with new technologies.

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Featured Articles

What is EaaS and What Value Can it Bring?

Connected products allow OEMs to move from equipment makers with one customer touch point at the initial sale to a more dynamic role over the long term as an interactive partner with their customers via an EaaS model of operations.

Meet business-wide goals with Equipment as a Service

Equipment as a Service (EaaS) is an industrial Internet of Things (IoT) solution that doesn’t just increase recurring revenue, it opens the door to more business opportunities.

Features-as-a-Service: Paywalls are Not Just for Content

OEMs can generate predictable and recurring monthly revenues by offering Features-as-a-Service in any connected equipment or product.

How Connected Products Enable Predictive Maintenance

Using analytics and AI, OEMs of connected equipment can gain a deep understanding of the status of a machine and move to a predictive maintenance mode of operation.

Remote Condition Monitoring and Remote Service: Keys to Efficient Service Delivery for Service Teams

Companies are turning to remote service and condition monitoring to cut costs, make more efficient use of service staff, and vastly improve the operations of their equipment in the field.

Performance Monitoring: Challenges, Solutions, and Benefits

A look at how IoT and analytics can improve and enhance the performance monitoring of industrial equipment and processes.

How AI Will Make Industry 4.0 Profitable

The ability to move to Industry 4.0 depends on an organization’s ability to scale its proofs of concept to a more industrialized level.

The Benefits of Analytics-Based Product Engineering

A look at how system simulation and IoT capabilities can close the data feedback loop.

Out of the Frying Pan and into the Connected Kitchen

How data and artificial intelligence are ready to revolutionize the restaurant kitchen.

Everything-as-a-Service: Manufacturers Offering Post-Sale Maintenance Likely More Profitable

IFS reports that manufacturers which offer aftermarket service are 24 percent more likely to report a profit than those which offer reactive service work.

How Asset-Heavy Industries Can Bridge the Gap Between Data Collection and PdM

Certain asset-heavy industries like utilities know the need to collect real-time operational data for maintenance. How do you do this efficiently?

Predictive Maintenance: Often the Right Solution to the Wrong Problem – For Now

The secret to using predictive data is often finding clear, quick wins. And those wins may come in unexpected places rather than from the applications that are generating the most buzz and the most headlines in industry publications.

Gaining Visibility to Address What If’s Before Disruptions

Learning to manage increasingly complex systems and avoid disruptions is only possible with clear visibility on every piece of the business.

Additiopnal Resources

Generating New Revenue Streams with Equipment as a Service (Webinar)

Have you ever wished that you can generate recurring revenue and secure your business relationships for the long-term?

Change the service game with connected products (White Paper)

Machine builders and original equipment manufacturers (OEMs), particularly those with globally-distributed fleets, are facing the ‘yin and yang’ of growth and competition.

AI in IoT is transforming manufacturing

Futurum’s principal analyst Shelly Kramer talks with Dr. Alexandr Sadovoy, Solution Architect for MindSphere products at Siemens, about the challenges facing manufacturing organizations today, and how artificial intelligence (AI) in IoT is transforming manufacturing.

The Benefits Of Artificial Intelligence (Ai) And Machine Learning (Ml) In Manufacturing

Data is a new business asset for many companies, especially manufacturing companies. These organizations’ manufacturing processes produce massive amounts of data each day. That data presents a powerful opportunity for competitive advantage—as long as it’s used to its full potential.

Improving Service and Profits with Connected Products

Any company that sells or maintains an industrial or consumer product in the field can benefit from ubiquitous connectivity that enables it to collect and analyze the vast amount of data those devices generate. It does not matter what type of equipment is involved. It can be a printer in an office, an MRI unit in a hospital, a refrigerated truck on a highway, a wind turbine in a remote ocean location, a robotic assembly unit on a production line, or something else. Different groups with access to the wealth of data such industrial equipment produces can implement new business models and change how companies interact with their customers. They can also increase service levels to their users and form long-term relationships.

Additionally, in an environment of highly connected devices, companies have an opportunity to offer Equipment as a Service (EaaS) and Features-as-a-Service, enabling recurring revenue streams and a sustained relationship with the customer (vs. a one-time transaction). While subscription models are well known in the software arena, they can now be realized with hardware as well, thanks to the flow of data from the devices and other sources.

Such data and insights derived from a connected product can also help increase product availability (e.g., via remote monitoring and predictive maintenance) and speed problem resolution.

Why is all of this so important and why now? The missing link in most companies preventing this move to a modern, data-driven industrial products approach is a lack of workers with the data science skills to make sense of the data and unlock its value. What’s needed is easy access to Al, so-called AI for all.

Once those elements are in place, there is a wide range of applications and use cases for connected products.

Connected Products Use Case 2: Remote Monitoring

Companies are turning to remote service and condition monitoring to cut costs and make more efficient use of service staff. For years, equipment manufacturers mostly focused on selling their machines and considered service as a secondary item to be offered. That was fine until competition from lower-price providers started to emerge. Now, merely selling machines alone is no longer profitable – service has become a differentiating factor.

The problem is that service does not scale well. Service efforts are labor-intensive and expensive. Dispatching workers to every customer site is impractical. Connected products offer an alternative. OEMs of connected products typically have a wealth of data about equipment as it is being used. That data can be collected, viewed, and analyzed centrally.

Remote monitoring proved valuable during the pandemic when people were barred from facilities. Now, its capabilities come in handy for equipment in remote locations. That could be anything from a wind turbine in the middle of an ocean or a power grid transformer in a mountainous region.

With remote monitoring, a service organization can assess what equipment needs service and what type of skills will be needed to be deployed to the site. Such capabilities alone save money and improves the efficiency of a service team. No longer is a technician dispatched to a site to diagnose a problem only to find out he or she does not have the right tools, spare parts, or expertise to perform the maintenance.

Connected Products Use Case 3: Predictive maintenance

One of the greatest benefits of connected products is the wealth of data available about their operation and health. Companies can use that data about the product (and combine other data such as its location, service record, operating environment, etc.) to gain insights into the product’s operating status and performance to modernize their maintenance operations.

Traditional approaches to maintenance that wait for something to go wrong are incredibly bad for business. Downtime is incredibly expensive. And replacing parts based on manufacturers’ calendar-based maintenance schedules can result in good parts being replaced well before they fail.

Analysis of data from connected equipment can help identify problems in the making or spot analogies that require additional attention. Compared to calendar-based asset replacement, predictive maintenance is much more effective at preventing downtime while getting the maximum life out of a part or piece of equipment.

A critical aspect of predictive maintenance is identifying parts or equipment that are likely to fail before their scheduled replacement and maintenance time. The true benefit comes when artificial intelligence is used to detect a potential problem. If such intelligence is used by an expert system, alerts can be sent before problems occur, and corrective action based on derived information about the part or product can be delivered to those charged with maintaining equipment.

An additional benefit of adopting remote monitoring and predictive maintenance for connected products is that once insights are derived, the OEM may be able to make changes (e.g., reset the product or update its software) without actually visiting the site.

Connected Products Use Case 4: Features-as-a-Service

Any feature of a piece of connected equipment that is controlled by software can be made selectively available. That allows OEMs to generate predictable and recurring monthly revenues by offering Features-as-a-Service in any connected equipment or product.

One advantage is that an OEM only needs to build and sell one model. They can then offer different versions with richer feature sets for higher sale prices. If a customer chose a higher-end set of features, they would pay a higher price. That model then replaces the approach where, say, an industrial device is built and sold in two, three, four, or more versions, each with different features and configurations.

Another approach that is being taken with Features-as-a-Service is to offer premium features that are software enabled on a subscription basis. An example would be industrial printers or medical scanners with different resolution modes. The unit might be sold offering one level of printing quality or scanning resolution. The customer could then be offered the higher-level capabilities for a monthly fee. In essence, the OEM is offering quality-as-a-service.

An additional way to offer Features-as-a-Service is to partner with a third-party software vendor to enhance the capabilities of the original product or device. For example, an MRI or CT scan manufacturer might offer AI-based image analysis as an extra.

A Final Word

Connected products offer many opportunities for OEMs to innovate. It does not matter if the product is for the industrial or consumer market. Built-in connectivity provides a conduit into the customer’s realm.

Shared operational and status data can be used to look for problems in the making. Connectivity affords a way to gather that data without a site visit. And the connectivity allows fixes (e.g., a product reboot, installation of new software, etc.) to be done remotely. Analysis of the data can lead to improved service and higher availability via predictive maintenance.

Additionally, new business models can be supported, ranging from equipment-as-a-service to features-as-a-service.

The bottom line: connected products allow OEMs to move from equipment makers with one customer touch point at the initial sale to a more dynamic role over the long term as an interactive partner with their customers.