{"id":13348,"date":"2022-03-13T10:59:23","date_gmt":"2022-03-13T09:59:23","guid":{"rendered":"https:\/\/advancedfleetmanagementconsulting.com\/eng\/?p=13348"},"modified":"2022-03-13T10:59:23","modified_gmt":"2022-03-13T09:59:23","slug":"data-11","status":"publish","type":"post","link":"https:\/\/advancedfleetmanagementconsulting.com\/eng\/2022\/03\/13\/data-11\/","title":{"rendered":"How to use all that sensor data to improve fleet productivity, ROI"},"content":{"rendered":"

From the front bumper to the trailer doors, trucks and other fleet vehicles are getting more \u2018sensorized\u2019 each year. If analyzed correctly, that sensor data can help companies predict maintenance needs and other outcomes to keep vehicles moving.<\/span><\/p>\n

Thanks to a growing number of sensors, an absurd amount of data is being generated on today\u2019s commercial vehicles. The fleets that learn how to harness that data can create better connections between shops and the aftermarket. And if it\u2019s done right, it could lead to better uptime for fleets of all sizes.<\/span><\/p>\n

\u201cBumper to bumper in a truck, in a trailer, in off-highway equipment, a van, bus\u2014any commercial vehicle you can think of\u2014systems are getting \u2018sensorized,\u2019\u201d Sandeep Kar, chief strategy officer for Noregon<\/a>, said during a recent Heavy-Duty Aftermarket Week (HDAW<\/a>) 2022 panel. \u201cOEMs and Tier Ones are putting these sensors in these systems that are capturing massive amounts of data.\u201d<\/span><\/p>\n

Kar said the data bidirectionally transmitted by modern \u2018sensorized\u2019 commercial vehicles\u2014between the fleets, OEMs, and telematics providers\u2014can also be used to \u201cpredict certain outcomes.\u201d<\/span><\/p>\n

\u201cWe can now pinpoint what\u2019s wrong with that vehicle,\u201d Kar explained. \u201cTechnology exists today to guide that vehicle towards a service and maintenance location, [which] now knows this particular vehicle is coming in with this particular part requirement and service requirement. That reduces dwell time.\u201d<\/span><\/p>\n

Ben Johnson, director of product management for Mitchell 1<\/a>, joined Kar to discuss how data will lead the way to predictive maintenance<\/a>, and ultimately a better connection between shops and the aftermarket\u2014resulting in better uptime for fleets.<\/span><\/p>\n

Following truck data from coast-to-coast<\/span><\/h3>\n

Johnson posed a common scenario of a coast-to-coast vehicle developing a problem in the middle of the country. If that vehicle is transmitting data, to say a fleet management system, that data can be evaluated through services that recognize codes, the general causes of such codes, the severity of codes, vehicle operational safety based on present codes, and more.<\/span><\/p>\n

\u201cWe know enough about the code that we can direct [that vehicle] to a known shop,\u201d Johnson explained. \u201cWe know the parts that are most likely going to be needed, [and can] get those parts on their way to that shop, [and] make sure that that shop has the right technician, so that very quickly, the truck can show up, the part is there, the technician just changes that part, verifies it, that resolves the issue, and gets the driver on the way. But information is what makes that scenario possible.\u201d<\/span><\/p>\n

Without such data, Johnson said that a driver would have to arrive at the shop and wait for a scan tool to be plugged into the vehicle only to begin the service process from there. But with today\u2019s available data, Johnson explained, \u201cthe process can start way upstream by using that information.\u201d<\/span><\/p>\n

This is the stage where the aftermarket has an advantage that they can capitalize on, Kar said, by providing the parts and services to reduce dwell time.<\/span><\/p>\n

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\"Diagnostics<\/span><\/div>\n<\/div>
Diagnostics provider Noregon Systems has started to use data to help fleets become more prognostic in their maintenance, fixing problems before they lead to downtime.<\/span><\/figcaption><\/figure>\n<\/div>\n<\/div>\n<\/div>\n

Data and the fleet industry\u2019s \u2018ticking time bomb\u2019\u00a0<\/span><\/h3>\n

While it can be easy to collect all this data, it\u2019s what fleets do with it that gives it power. Think of algorithms as the engine for this predictive strategy, and data the fuel<\/a>. And the CV repair space is on the verge of crossing over to this predictive maintenance phase.<\/span><\/p>\n

Though, this influx of data advancement has implications for what Kar referred to as \u201ca ticking time bomb.\u201d<\/span><\/p>\n

\u201cOur industry talks a lot about driver shortage; we don\u2019t talk enough about technician shortage<\/a>,\u201d Kar said. \u201cAnd that\u2019s a huge problem. These vehicles are getting more and more complicated, more and more \u2018sensorized,\u2019 and we don\u2019t have enough skilled technicians.\u201d<\/span><\/p>\n

Kar reinforced this statement with reference to a statistic claiming that the average age of a technician in the industry is 46 years old, alluding to a sentiment that not enough new technicians are entering the industry.<\/span><\/p>\n

Kar continued on the rise in \u2018sensor-ization\u2019 and its positive impacts, stating that today\u2019s vehicles are transmitting data to the fleet, to telematics companies, to the OEMs, as well as establishing a bidirectional data transfer from infrastructure, from the OEMs, from fleets, and more.<\/span><\/p>\n

Creating a service solution out of data<\/span><\/h3>\n

How is it that the CV industry can reach this integrated service solution across parties? Connectivity.<\/span><\/p>\n

Through the connection of databases and the use of application programming interfaces (APIs), fleets, OEMs, telematics providers, the aftermarket, and others can converge on solution delivery.<\/span><\/p>\n

\u201cOnce you have that connectivity, the entire ecosystem gets visibility into that particular problem,\u201d Kar said. \u201cThen a lot of new ways of engaging with warehouse distributors, or service and maintenance providers, IRFs, becomes possible because everybody can now start bidding for that business as we socialize or democratize that information. Yet, as an industry, it can\u2019t be done by just companies like ours; we have to have the entire aftermarket joining into this.<\/span><\/p>\n

\u201cAnd the good thing is that because the systems are getting \u2018sensor-ized\u2019, data is getting generated, this is bound to happen,\u201d Kar continued. \u201cIt\u2019s just a matter of time. And so, we are ready for it. And we invite the industry to join us in this.\u201d<\/span><\/p>\n

Leveraging AI for better parts insight<\/span><\/h3>\n

Johnson explained Mitchell 1\u2019s use of AI with their database to achieve their analytical insight for parts repair and replacement.<\/span><\/p>\n

\u201cWe have a history with light vehicles that have over one billion repair orders that we analyze every day with our AI systems to create insights,\u201d he said. \u201cSo, we can say, \u2018For this vehicle with this trouble code with this many miles, it\u2019s probably this thing that caused that.\u2019 We can do that on the heavy-duty side, too. To be fair, we\u2019ve only got about 5 million repair orders in that out of the billion, but it\u2019s coming together. And so, people that really want to engage, want to make this stuff happen, can work with companies like ours, with Noregon\u2019s, with others that have these types of types of technologies.\u201d<\/span><\/p>\n

Once this data integration is established, analysts can truly understand and in turn actuate preparation and execution for imminent repairs and failures, coordinating parts procurement and services, Johnson explained.<\/span><\/p>\n

\u201cThese technologies\u2026it\u2019s here. It\u2019s not coming, it\u2019s here,\u201d he said. \u201cIt takes people to help understand what it is you\u2019re trying to accomplish. And then we can set up the relationships to make that happen. APIs are ultimately the transmission methods that move the data around and deliver it in a way that makes your fleets operate better.\u201d<\/span><\/p>\n

\u201cWe talked about APIs and preventive maintenance, that both of our organizations develop and offer; the solutions are available, but the reliability [of] the solutions need to be proved,\u201d Kar commented. \u201cThat will happen once you have sufficient critical mass of data that is available coming from these vehicles because to train an AI model, the more data you have, the better the reliability and accuracy of those predictions. This is a movement that is happening in [the] early days. But as it starts gaining momentum, you will see that the market matures to a stage where the model has been proven. The connections have been made through APIs. Part visibility has increased. The part flow has increased. Dwell time has decreased. And then, it takes on a life of its own.\u201d<\/span><\/p>\n

Both Kar and Johnson agreed, to make this a functioning reality in the industry, it will take communication. Establishing relationships between fleets, OEMs, diagnostic, telematics, and service information providers, aftermarket parts suppliers, and everyone in-between and leveraging those connections to share their data and needs will ultimately result in a predictive maintenance environment.<\/span><\/p>\n

\u201cThe information is there,\u201d Johnson concluded. \u201cWe could feed these systems and do some cool things with them. The problem is, they\u2019re all in ponds. They\u2019re not in a big data lake. And [when] we can get more of a mass of that information, the better it [will] become. But the capabilities are here today. It\u2019s just a matter of really feeding, training, and then outputting that information and putting in the connections. It\u2019s here. It\u2019s a pretty exciting time.\u201d<\/span><\/p>\n

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By Tyler Fussner<\/a><\/span><\/p>\n

Source https:\/\/www.fleetowner.com\/<\/a><\/p>\n

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From the front bumper to the trailer doors, trucks and other fleet vehicles are getting more \u2018sensorized\u2019 each year. If analyzed correctly, that sensor data can help companies predict maintenance needs and other outcomes to keep vehicles moving. Thanks to a growing number of sensors, an absurd amount of data is being generated on today\u2019s…<\/p>\n","protected":false},"author":3,"featured_media":13349,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[18],"tags":[39],"_links":{"self":[{"href":"https:\/\/advancedfleetmanagementconsulting.com\/eng\/wp-json\/wp\/v2\/posts\/13348"}],"collection":[{"href":"https:\/\/advancedfleetmanagementconsulting.com\/eng\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/advancedfleetmanagementconsulting.com\/eng\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/advancedfleetmanagementconsulting.com\/eng\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/advancedfleetmanagementconsulting.com\/eng\/wp-json\/wp\/v2\/comments?post=13348"}],"version-history":[{"count":1,"href":"https:\/\/advancedfleetmanagementconsulting.com\/eng\/wp-json\/wp\/v2\/posts\/13348\/revisions"}],"predecessor-version":[{"id":13350,"href":"https:\/\/advancedfleetmanagementconsulting.com\/eng\/wp-json\/wp\/v2\/posts\/13348\/revisions\/13350"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/advancedfleetmanagementconsulting.com\/eng\/wp-json\/wp\/v2\/media\/13349"}],"wp:attachment":[{"href":"https:\/\/advancedfleetmanagementconsulting.com\/eng\/wp-json\/wp\/v2\/media?parent=13348"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/advancedfleetmanagementconsulting.com\/eng\/wp-json\/wp\/v2\/categories?post=13348"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/advancedfleetmanagementconsulting.com\/eng\/wp-json\/wp\/v2\/tags?post=13348"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}