M2M and IoT helps to transform businesses

    In the world of maintenance, rental and field service integrating Machine 2 Machine (M2M) communication and remote diagnostics technologies help to improve equipment up-time and first-time fix rates. Additional services are only recently being recognized as a major opportunity for growth. This means that many operations are today being managed with increasingly outmoded or insufficient technologies. This really creates a big opportunity for early adopters to differentiate themselves. Customer service can be optimized through successful implementation of cutting edge software, centralizing disparate operations and collecting big data more efficiently. Recent research showed 40% of survey respondents reported a first-time fix rate of 85% or higher, while 26% of the respondents said that their first-time fix rate was between 75-80%. In order to improve on these numbers, companies need to create better triage and diagnostic practices at a dispatch level, as well as field based access to parts. When combined with optimized scheduling, this can help avoid missing parts being the reason for missing a first-time fix opportunity. The technology infrastructure needed to effectively manage these processes must be integrated with back office CRM and ERP suites in order to create visibility across all stages of the service lifecycle, a step towards the Internet of Things.

    So what is the difference between M2M and IoT?
    M2M is defined as the communication between a machine or device and a remote computer. M2M is about connecting a device to the cloud, managing that device, and collecting machine and sensor data. In essence, M2M is about connecting and communicating with a ‘thing’ where a thing can be a machine, device, or sensor — basically anything that can send data.

    IoT (Internet of Things) goes beyond M2M — beyond computers connecting to things. IoT represents things connecting with systems (including business applications, like ERP, CRM and PLM systems, analytics systems, data warehouses, and control systems), people (including workers, consumers, employees, partners, and customers), and other things (including machines, devices, sensors, consumer products, vehicles, etc.). By connecting machines, work pieces and systems in a cloud first, mobile first world, we are creating intelligent networks along the entire value chain that can control each other autonomously. As seen by the IoT examples above, machines predict failures and trigger maintenance processes autonomously or self-organized logistics that react to unexpected changes in the production.

    So, does this change the classic manufacturing and services value chain? For sure the world of production will become more and more networked until everything is interlinked with everything else. It also means that the complexity of production and supplier networks will grow. Networks and processes have so far been limited to one factory. But in an Industry 4.0 scenarios, these boundaries of individual factories will no longer exist. Instead, they will be lifted in order to interconnect multiple factories or even geographical regions.

    In current disconnected industry environments, providing high-end quality service or product at low cost is the key to success and industrial factories are trying to achieve as much performance as possible to increase their profit as well as their reputation. In this way, various data sources are available to provide worthwhile information about different aspects of the factory. In this stage, the utilization of data for understanding the current condition and detect faults and failures is an important topic to research. e. g. in production, there are various commercial tools available to provide OEE (Overall Equipment Effectiveness) information to factory management in order to highlight root cause of problems and possible faults in the system.

    In an IoT or Industry 4.0 factory, in addition to condition monitoring and fault diagnosis, components and systems are able to gain self-awareness and self-predictiveness, which will provide management with more insight on the status of the factory. Furthermore, peer-to-peer comparison and fusion of health information from various components based on machine learning provides a precise health prediction in component and system levels and enforce factory management to trigger required maintenance at the best possible time to reach just-in time maintenance and gain near-zero downtime. The basic starting point is connected products that generate alerts and notifications based on sensor readings, like JJ Foods is doing. More advanced solutions allow remote operation using sensors. And the most mature solutions allow organizations to use sensor data to provide customers with high-value performance improvement insights.

    IoT really can impact businesses as demonstrated by the examples above. Gartner reports that by 2020, there will be 26 billion connected devices in the world. And in a report WBR Field Service released recently, 42 percent of the field service respondents that participated, identified remote diagnostics as the number one area of spend over the next six to 12 months.

    M2M and IoT helps transform businesses. Philips is a good example of a company transforming business. When Philips announced the 2013 financial results Washington Metropolitan Area Transit Authority (WMATA) in Washington D.C. announced a ten-year contract with Philips Lighting to upgrade lighting in 25 parking garages using energy-efficient LEDs and adaptive controls. The project started in March 2014 and is unique in that Philips will supply the solid-state lighting (SSL) system using a lighting-as-a-service model. The project will also utilize daylight harvesting and adaptive controls to maximize energy savings while maintaining a safe and secure environment. The project includes replacement and maintenance of the lights. Besides the significant savings of energy there is another thing which caught my attention. Most US cities show interest in this, but don’t have the money. Philips is advancing the investments by changing the business model. Philips traditionally seen as a technological manufacturing company providing superior products with very bad marketing is now transforming into a company providing technical professional services. Of course they still produce the lights, but the margin is not on selling the products anymore. It is on selling a long term contract and managing the performance of that contract. With that Philips is following the IBM strategy and with Lighting following the strategy they have already implemented in their healthcare division including the financing. The strategy is very different to the strategy of one of their competitors like Sony. Of course the enabling of this business transformation could be supported by our service management software.

    The transition from reactive to proactive service will continue. Machines talking to machines is a great advancement; however, true value will be achieved when organizations use the data to resolve issues more efficiently and, moreover, avoid failures in the first place.

    The IoT represents the next evolution of the digital universe. The speed at which nimble start ups and Internet players are capturing IoT opportunities should serve as a wake-up call to larger, traditional organizations as well as to Dynamics Software. Analyst estimates point to a world where start ups will dominate the IoT market. Fifty percent of IoT solutions are expected to originate in start ups less than 3 years old, by 2017.

    (extract from Eric Veldkamp’s blog)

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