Start driving decisions with machine data.
Categories:

     

    An issue in manufacturing that is singular to OEM is the speed with which they can respond with service to the machines, in the case of a failure. In the past, this has usually meant an actual failure has taken place, resulting in delayed order, waste of lower quality parts and so on.

    Service teams are dispatched and repairs / replacement of parts are made, but all of this takes time and creates more delay. As far as being able to predict the need for maintenance, traditional systems meant using the historical information about the machine, or simply establishing maintenance schedules, whether or not they were needed.

    Now imagine a world where machines can be monitored remotely, providing an unprecedented service level. The ability to gather real-time data and alert customers about impending issues, before any damage is done to an order is valuable.

    “Industry 4.0 software provides analytical tools that help OEMs understand the mechanical  factors and environmental conditions that lead to machine failures. Whether it’s vibration, temperature, pressure or other performance indicators, OEMs can use this software to analyze the machine data gathered from their IoT-enabled machines to perform predictive maintenance.” (Source)

    Remote machine monitoring as an extension of machine service options

    In fact, remote machine monitoring, enabled by industrial IoT, is the unique selling proposition that OEM and other equipment providers can offer to their clients, as part of the post sale service package. This business model is otherwise known as Equipment-as-a-Service.

    “...equipment manufacturers can transform their approach to service with the ability to see, understand and take action on their customer’s real-time machine data from anywhere at any time.” (Source)

    Reducing downtime, particularly unplanned downtime, is an essential part of keeping costs down and manufacturing levels up. Remote machine monitoring can collect data about the operations of any given unit and transmit that data back via the cloud, enabling OEMs to provide peak level service response time.

    While historically, this servicing would require a lengthy and costly on-site visit and possible investigation as to the issues being experienced. A maintenance team would not necessarily be able to detect at a glance which parts were malfunctioning, resulting in a manual process of checking each par. Instead, a remote monitoring system enables OEMs to visualize the issues via the data from anywhere. Troubleshooting even the slightest alteration in a tool path can be done quickly and easily.

    Beyond service response is the ability to predict and even prevent breakdowns that severely impact a manufacturer’s production cycle by reviewing and analyzing the data produced. With predictive maintenance, OEMs can review available data, detect any exceptions or historical patterns and service the machines in advance of a problem occurring, limiting the impact. It also ensures that a manufacturer need not maintain an extensive inventory of replacement parts, but rather work on a just in time basis.

    “Service departments can use data to gain insight into customers’ equipment health and condition, identify maintenance opportunities with analytics and reporting, predict and deliver early warning of potential equipment failures, highlight elevated risk areas that lead to machine downtime, or even take preventative action before it impacts a customer’s machine performance.” (Source)

    diagnosticstablet

    Challenges with remote monitoring

    Industry 4.0, and its vast changes to the way legacy processes such as what many manufacturers will have, bring challenges to the forefront. This is particularly true when dealing with data across organizations.

    •        Data integrity due of the remote access.
    •        Cybersecurity for the network.
    •        The ability of the software to work with different machines; manufacturers being unwilling to entertain           different IoT solutions for different machines, to say nothing of inaccuracy in discovering the root                   cause of a problem should it be in a related machine that is not monitored.

    SaaS platforms—such as MachineMetrics—address all of these issues, including the ability to encrypt data before transfer and an easy self-installed interface with a range of machines, enabling manufacturers to limit their concern about having to use different monitoring solutions on their factory floors.

    The future opportunities for OEMs, beyond predictive maintenance

    The ability to identify service opportunities and measure ongoing process improvements, such as ongoing machine health monitoring, is important to after sales service but take innovation a step beyond into the realm of future design specifications!

    OEM and equipment manufacturers will be able to leverage the data that they receive from their customers to improve on their existing designs or even create better, more enhanced machines because they will have easy access to the data that shows them how the equipment is being used. This presents a huge opportunity for the OEM to ensure that they stay ahead of their competition.

    With industrial IoT in the mix, the OEM / equipment manufacturing industry has an amazing opportunity to provide real value-add to their service packages, making them indispensable to the manufacturers they service.

    Want to learn more? Contact us to learn more. 

     

    Comments

    Leave a comment

    Subscribe to our mailing list

    Related posts

    Data Driven Manufacturing: Benefits, Challenges, and Strategies

    Data Driven Manufacturing: Benefits, Challenges, and Strategies

    Optimizing Production Efficiency through Data-Driven Manufacturing Strategies Although diverse data capturing technologies exist, manufacturers still struggle to use them. It's due to this major chall...

    MachineMetrics
    MES vs. IIoT Platform: Why Not Both?

    MES vs. IIoT Platform: Why Not Both?

    Is an MES or IIoT Platform (or Both) the Best Option for You? The increasing use of industrial automation in process and discrete manufacturing facilities have put the manufacturing execution system (...

    MachineMetrics
    A Manufacturer's Guide to Edge Computing

    A Manufacturer's Guide to Edge Computing

    Below is what we will cover in this in-depth article on edge computing in manufacturing. Select a link if you would like to jump to a particular section:

    MachineMetrics
    A Long-Term Strategy for Manufacturers Adopting Industry 4.0

    A Long-Term Strategy for Manufacturers Adopting Industry 4.0

    It’s not uncommon for a factory to operate several generations of the same type of production equipment within a single factory. Except for extremely large companies with very deep pockets, most compa...

    MachineMetrics
    MachineMetrics, World Economic Forum Join Forces to Support Sustainable Future for Manufacturing

    MachineMetrics, World Economic Forum Join Forces to Support Sustainable Future for Manufacturing

    Boston, MA -- MachineMetrics, a leading data and digital app platform for manufacturing, today announced that it has joined the World Economic Forum’s Global Innovators Community, a group of the world...

    MachineMetrics
    The Downside to Do-It-Yourself IoT

    The Downside to Do-It-Yourself IoT

    The digital transformation of industrial production enterprises relies on the internet of things (IoT) for connectivity, visibility, and deeper insight into performance. And although the success of In...

    MachineMetrics
    5 Steps to Bring Your Legacy Systems Online with IIoT

    5 Steps to Bring Your Legacy Systems Online with IIoT

    The move to industry 4.0 will be defined by how effectively legacy systems and assets within shop floors are integrated into online or cloud platforms. This is because a large percentage of enterprise...

    MachineMetrics
    Finding the Payback for Smart Manufacturing

    Finding the Payback for Smart Manufacturing

    Industry 4.0 is defined by smart manufacturing processes such as data-driven plant optimization, industrial automation, and predictive maintenance. Since these processes rely on shop floor data, confi...

    MachineMetrics
    Industrial IoT Security: Challenges and Solutions

    Industrial IoT Security: Challenges and Solutions

    With 2020 firmly underway, the exponential growth of Industrial IoT is on track with recent predictions.  And as we head toward a world with over 75 billion connected devices by 2025, almost a third w...

    MachineMetrics