Michael Riemer

The true cost of equipment downtime or poor asset maintenance goes far beyond the dollar amount you see on the repair invoice. Indeed, an asset’s downtime can have a significant impact on your organization’s bottom line. A malfunctioning piece of factory equipment or a broken-down commercial vehicle can result in lost revenue, additional costs and even regulatory fines.

Ineffective service management has shown to increase downtime as well as costs. For many commercial and industrial… Show more

The true cost of equipment downtime or poor asset maintenance goes far beyond the dollar amount you see on the repair invoice. Indeed, an asset’s downtime can have a significant impact on your organization’s bottom line. A malfunctioning piece of factory equipment or a broken-down commercial vehicle can result in lost revenue, additional costs and even regulatory fines.

Ineffective service management has shown to increase downtime as well as costs. For many commercial and industrial assets, phone, email, paper and siloed applications negatively impact service-management efficiency—increasing downtime, reducing profitability, and lowering operational efficiencies. The tsunami of connected asset data has renewed awareness and interest in improving asset performance and availability, but this flood of data has done little to solve these service-process challenges. Show less

Making sensor data actionable, improves uptime and helps companies realize the potential of IoT investments.

The big data explosion has presented companies with an interesting juxtaposition. Organizations possess an enormous amount of information upon which to base better business decisions, but they’re challenged with being able to share and interpret this data—to make it actionable—in order to reach effective outcomes.

As the Industrial Internet of Things steps out of the shadows and sheds the chains that have kept data from being holistically actionable, we're seeing the beginning of a new commercial asset-management paradigm.

In 2016, the Internet of Things went mainstream, but in 2017 we expect the Industrial Internet of Things (IIoT) to transform operations across numerous industries. Also known as the Industrial Internet, the IIoT enables machine-to-machine (M2M) communication of usage… Show more

As the Industrial Internet of Things steps out of the shadows and sheds the chains that have kept data from being holistically actionable, we're seeing the beginning of a new commercial asset-management paradigm.

In 2016, the Internet of Things went mainstream, but in 2017 we expect the Industrial Internet of Things (IIoT) to transform operations across numerous industries. Also known as the Industrial Internet, the IIoT enables machine-to-machine (M2M) communication of usage, performance and health metrics. There is quite a buzz around using this data, along with machine learning and other predictive algorithms, to help anticipate and eliminate potential causes of downtime.

Nowhere is this more evident than in the commercial asset service ecosystem. Trucking fleets, construction assets, agriculture and power-generation equipment are all susceptible to costly unscheduled downtime and generally long repair cycles. Show less

The manufacturing industry is using the Industrial Internet of Things (IIoT) as a driver for innovation and digital transformation. It’s a market that’s expected to grow at a furious rate. According to BI Intelligence, the installed base of manufacturing IoT devices is set to swell to 923 million devices in 2020 with manufacturers spending approximately $267 billion on IoT.

The benefits are multiple. IIoT sensors can be used to track the location and performance of factory machinery… Show more

The manufacturing industry is using the Industrial Internet of Things (IIoT) as a driver for innovation and digital transformation. It’s a market that’s expected to grow at a furious rate. According to BI Intelligence, the installed base of manufacturing IoT devices is set to swell to 923 million devices in 2020 with manufacturers spending approximately $267 billion on IoT.

The benefits are multiple. IIoT sensors can be used to track the location and performance of factory machinery, tools and assets, monitor ambient temperature and pressure and gauge machine utilization. The data that’s derived from those sensors can then be aggregated, prioritized and used to predict and quantify the severity of issues and eventually predict potential equipment failures.

But having access to this information alone is not enough. Information is most valuable in these situations when it can be easily acted upon and used as part of a closed-loop, service event management process. Show less

The Cloud is fast becoming a springboard for innovation in the manufacturing industry, with plants and factories already reporting good results from Cloud-based applications.

Industrial facilities are seeing benefits such as lower costs, greater efficiencies due to process automation, increased data visibility, reduced total cost of ownership, and better, faster data integration capabilities over legacy systems.

It’s no surprise that Cloud use is also expected to dramatically… Show more

The Cloud is fast becoming a springboard for innovation in the manufacturing industry, with plants and factories already reporting good results from Cloud-based applications.

Industrial facilities are seeing benefits such as lower costs, greater efficiencies due to process automation, increased data visibility, reduced total cost of ownership, and better, faster data integration capabilities over legacy systems.

It’s no surprise that Cloud use is also expected to dramatically accelerate this year. A key driver for this growth is in the use of Cloud synergies, mobility, and advanced analytics as the fabric for analyzing data coming from the factory floor and converting it into actionable information that is accessible for all decision makers. According to IDC Manufacturing Predictions, by the end of 2017, 50 per cent of manufacturers will use the Cloud for this purpose.

A significant source of this data is from the Industrial Internet of Things (IIoT) — sensors and devices located on machines and equipment which track everything from temperature to utilization, and could be used to predict potential equipment failures. Having access to that data in an actionable and contextual format is key to delivering true organizational value. Show less

The construction industry has become increasingly reliant upon connected data through the Industrial Internet of Things (IIoT). The Association of Equipment Management Professionals (AEMP) has even produced an ISO-certified data schema for exchanging worksite data from connected assets independent of manufacturer.

Industry leaders such as Caterpillar, Volvo Construction, Deere and Komatsu are making significant investments in connected sensors to collect data on engine performance… Show more

The construction industry has become increasingly reliant upon connected data through the Industrial Internet of Things (IIoT). The Association of Equipment Management Professionals (AEMP) has even produced an ISO-certified data schema for exchanging worksite data from connected assets independent of manufacturer.

Industry leaders such as Caterpillar, Volvo Construction, Deere and Komatsu are making significant investments in connected sensors to collect data on engine performance, machine operations, asset tracking, power and fuel usage, idle time and fault codes and other information. However, like many other industries with increasing amounts of connected assets and growing concerns about downtime and total cost of ownership, the construction industry has had limited success in truly leveraging this information to its fullest potential. Show less

In 2016, the Internet of Things went mainstream, but in 2017 we expect the Industrial Internet of Things (IIoT) to transform operations across numerous industries. Also known as the Industrial Internet, the IIoT enables machine-to-machine (M2M) communication of usage, performance and health metrics. There is quite a buzz around using this data, along with machine learning and other predictive algorithms, to help anticipate and eliminate potential causes of downtime.

Nowhere is this more… Show more

In 2016, the Internet of Things went mainstream, but in 2017 we expect the Industrial Internet of Things (IIoT) to transform operations across numerous industries. Also known as the Industrial Internet, the IIoT enables machine-to-machine (M2M) communication of usage, performance and health metrics. There is quite a buzz around using this data, along with machine learning and other predictive algorithms, to help anticipate and eliminate potential causes of downtime.

Nowhere is this more evident than in the commercial asset service ecosystem. Trucking fleets, construction assets, agriculture and power-generation equipment are all susceptible to costly unscheduled downtime and generally long repair cycles. Show less

The need for always-on, efficient operations is key to the growth of the Industrial Internet of Things (IIoT), a market estimated to be worth $151.01 billion by 2020.

Companies from different industries — from automotive to construction and beyond – are investing in connected sensors to track the performance and health of their assets, the location of their fleets, and more.

While this is a good start, many organizations are not making effective use of this data. Teams continue to… Show more

The need for always-on, efficient operations is key to the growth of the Industrial Internet of Things (IIoT), a market estimated to be worth $151.01 billion by 2020.

Companies from different industries — from automotive to construction and beyond – are investing in connected sensors to track the performance and health of their assets, the location of their fleets, and more.

While this is a good start, many organizations are not making effective use of this data. Teams continue to share and store information in paper forms, spreadsheets, phone calls, and other legacy applications. Many of these teams are disconnected from one another and spend more time pushing paper – tracking maintenance schedules and histories, hunting down warranty information, or other time consuming tasks – than actually fixing equipment or keeping machines running. Show less

In this special guest feature, Michael Riemer discusses 5 steps for the commercial asset service industry to turn lots of raw, unfiltered data from the service event management process into reliable, actionable big data and ultimately a competitive advantage.

Traditionally, commercial asset maintenance has been fraught with headaches. Constant phone calls, voice mails, faxes, and other manual processes introduce costly inefficiencies across the service supply chain. In the trucking… Show more

In this special guest feature, Michael Riemer discusses 5 steps for the commercial asset service industry to turn lots of raw, unfiltered data from the service event management process into reliable, actionable big data and ultimately a competitive advantage.

Traditionally, commercial asset maintenance has been fraught with headaches. Constant phone calls, voice mails, faxes, and other manual processes introduce costly inefficiencies across the service supply chain. In the trucking business, for example, the average breakdown time for an asset is four days, of which less than 10% of the time is spent turning a wrench. The remainder is spent pushing paper, searching for warranty information, navigating siloed systems and applications, and chasing authorization and accountability. Show less