The OEM scenario is constantly changing. In the service sector, once focused on the tactical part of the product function, the new orientation now emphasizes how to strategically generate revenue and differentiate from competitors through the use of modern technology systems, includingIoT.
This kind of tension fosters a competitive environment in which OEMs feel a constant need to expand their offerings and provide customers with best-in-class equipment in order to build new partnerships and strengthen existing relationships. The fundamental measurement standard of this strategy is customer satisfaction. However, the importance of increased efficiency and productivity cannot be overlooked, nor the need to achieve adequate return on investment (ROI).
According to Bain’s projections, 6.8 million connected heavy construction machines will be sold between 2018 and 2025. It is clear that the future depends largely on the Internet of Things (IoT), which will enable enhanced data collection and analysis and overall innovation in this field. Like any other strategic investment, IoT investment must be evaluated; return on investment is, in this sense, an essential factor that the company must take into account before investing.
The top performance indicators for measuring IoT success for heavy equipment OEMs are:
- Exceptional Customer Experience
- Acquisition of the spare parts business
- Reducing costs and increasing productivity
- Service compliance and increase in the number of clients using it
- Reduced development costs
Let’s find out how IoT is able to improve OEM performance in these specific areas and how they relate back to an effective return on investment.
Nowadays, one of the essential aspects in achieving an exceptional customer experience is the need to make sure that customers’ time is given the right value and the highest priority. Predictive assistance enables this problem to be addressed. By leveraging the IoT to predict when a piece of heavy equipment needs repair or service, even under unexpected circumstances, OEMs can accurately manage and schedule downtime for machinery and equipment, thus offering their customers the best possible service.
Better service not only increases customer satisfaction, but also increases operational efficiency. The advantage of an IoT solution for heavy equipment is that it helps the user better understand the problem that needs to be analyzed from a remote location. In this way, technicians not only receive information, but also the assurance that they have the necessary equipment, components, and skills to solve the problem and achieve rapid recovery.
Providing accurate updates to service technicians also minimizes the process of meeting compliance requirements for companies with service level agreements. Integrated IoT sensors not only help in predictive machine servicing, but also enable automatic reports on asset status and alert when thresholds are reached. This feature greatly expands the possibilities for SLA satisfaction.
In addition to enabling remote monitoring, predictive maintenance detects possible failures in advance so that OEMs can take appropriate corrective measures at the right time to avoid unexpected interventions and unplanned downtime, thereby reducing project risks and costs. For OEMs, predictive maintenance data are useful in terms of quality defects. In fact, OEMs can keep track of failure history and implement corrective actions that will prevent unnecessary downtime for other customers due to unexpected quality defects.
Combining, storing and analyzing heavy equipment data is the so-called “deep learning” needed to take predictive maintenance to the next level. Data collected on heavy machinery allow OEMs to move from predicting a known possible failure to preventing it. This new knowledge is then incorporated to improve engineering knowledge, which, in turn, serves to refine model building. By taking this to the next level through better understanding of faults and their indicators, and by collecting more and more relevant data on the individual machine, OEMs are given the ability to shape the performance of individual machines in terms of operator utilization and environmental impact.
In addition to improving technical and design concepts, OEMs can leverage data from an IoT solution for heavy equipment to create different types of equipment, reducing simulations and the use of models. Using real data from an existing infrastructure, options for finding new designs or even new uses for equipment can lead OEMs to new markets and new product ranges. This gives OEMs the confidence to stay one step ahead of the competition.
OEMs realize that connected off-road equipment can help customers reduce costs, increase productivity and enhance safety. These services not only add value for OEM customers, but also strengthen brand loyalty, since other manufacturers’ equipment does not integrate an existing IoT solution. Parker provides Mobile IoT customers with an IoT solution focused just on them, capable of meeting the specific requirements of heavy equipment OEMs. By implementing Parker Mobile IoT, OEMs are able to generate additional revenue not only from their data-driven offerings, but also from their core business through increased equipment sales and after-sales services.
Why associate with Parker?
For OEMs, building an in-house IoT platform can be expensive and, moreover, take several years to develop. Working directly with Parker enables OEMs to benefit from comprehensive technology integration and data analytics expertise to devise valuable designs for customers without incurring the costs or risks associated with using an in-house solution. Click here to find out how Parker positively impacts OEMs around the world from an IoT perspective.
Article written by Clint Quanstrom, general manager IoT, and Kyri McDonough, director of marketing communications, Parker Hannifin Corporation.
Other related topics with the Parker Mobile IoT solution:
Parker Teams Deploying IoT to Help Customers Improve Operations
How IoT Systems Will Impact the Future for Off-Road Equipment
Modern Digital Ecosystems Take Mobile Hydraulic Systems to a New Level
The OEM scenario is constantly changing. In the service sector, once focused on the tactical part of the product function, the new orientation now emphasizes how to strategically generate revenue and differentiate from competitors through the use of modern technology systems, including IoT.
This kind of tension fosters a competitive environment in which OEMs feel a constant need to expand their offerings and provide customers with best-in-class equipment in order to build new partnerships and strengthen existing relationships. The fundamental measurement standard of this strategy is customer satisfaction. However, the importance of increased efficiency and productivity cannot be overlooked, nor the need to achieve adequate return on investment (ROI).
According to Bain’s projections, 6.8 million connected heavy construction machines will be sold between 2018 and 2025. It is clear that the future depends largely on the Internet of Things (IoT), which will enable enhanced data collection and analysis and overall innovation in this field. Like any other strategic investment, IoT investment must be evaluated; return on investment is, in this sense, an essential factor that the company must take into account before investing.
The top performance indicators for measuring IoT success for heavy equipment OEMs are:
Exceptional Customer Experience
Acquisition of the spare parts business
Reducing costs and increasing productivity
Service compliance and increase in the number of clients using it
Reduced development costs
Let’s find out how IoT is able to improve OEM performance in these specific areas and how these relate back to an effective return on investment.
Nowadays, one of the essential aspects in achieving an exceptional customer experience is the need to make sure that customers’ time is given the right value and the highest priority. Predictive assistance enables this problem to be addressed. By leveraging the IoT to predict when a piece of heavy equipment needs repair or service, even under unexpected circumstances, OEMs can accurately manage and schedule downtime for machinery and equipment, thus offering their customers the best possible service.
Better service not only increases customer satisfaction, but also increases operational efficiency. The advantage of an IoT solution for heavy equipment is that it helps the user better understand the problem that needs to be analyzed from a remote location. In this way, technicians not only receive information, but also the assurance that they have the necessary equipment, components, and skills to solve the problem and achieve rapid recovery.
Providing accurate updates to service technicians also minimizes the process of meeting compliance requirements for companies with service level agreements. Integrated IoT sensors not only help in predictive machine servicing, but also enable automatic reports on asset status and alert when thresholds are reached. This feature greatly expands the possibilities for SLA satisfaction.
In addition to enabling remote monitoring, predictive maintenance detects failures in advance so that OEMs can take appropriate corrective measures at the right time to avoid unexpected interventions and unplanned downtime, thereby reducing project risks and costs. For OEMs, predictive maintenance data are useful in terms of quality defects. In fact, OEMs can keep track of failure history and implement corrective actions that will prevent unnecessary downtime for other customers due to unexpected quality defects.
Combining, storing and analyzing heavy equipment data is the so-called “deep learning” needed to take predictive maintenance to the next level. Data collected on heavy machinery allow OEMs to move from predicting a known possible failure to preventing it. This new knowledge is then incorporated to improve engineering knowledge, which, in turn, serves to refine model building. By taking this to the next level through better understanding of faults and their indicators, and by collecting more and more relevant data on the individual machine, OEMs are given the ability to shape the performance of individual machines in terms of operator utilization and environmental impact.
In addition to improving technical and design concepts, OEMs can leverage data from an IoT solution for heavy equipment to create different types of equipment, reducing simulations and the use of models. Using real data from an existing infrastructure, options for finding new designs or even new uses for equipment can lead OEMs to new markets and new product ranges. This gives OEMs the confidence to stay one step ahead of the competition.
OEMs realize that connected off-road equipment can help customers reduce costs, increase productivity and enhance safety. These services not only add value for OEM customers, but also strengthen brand loyalty, since other manufacturers’ equipment does not integrate an existing IoT solution. Parker provides Mobile IoT customers with an IoT solution focused just on them, capable of meeting the specific requirements of heavy equipment OEMs. By implementing Parker Mobile IoT, OEMs are able to generate additional revenue not only from their data-driven offerings, but also from their core business through increased equipment sales and after-sales services.
Why associate with Parker?
For OEMs, building an in-house IoT platform can be expensive and, moreover, take several years to develop. Working directly with Parker enables OEMs to benefit from comprehensive technology integration and data analytics expertise to devise valuable designs for customers without incurring the cost or risk associated with using an in-house solution. Click here to find out how Parker positively impacts OEMs around the world from an IoT perspective.
Article written by Clint Quanstrom, general manager IoT, and Kyri McDonough, director of marketing communications, Parker Hannifin Corporation.
Other related topics with the Parker Mobile IoT solution:
Parker Teams Deploying IoT to Help Customers Improve Operations
How IoT Systems Will Impact the Future for Off-Road Equipment
Modern Digital Ecosystems Take Mobile Hydraulic Systems to a New Level
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