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    The Industrial Internet of Things (IIoT) space is trending, as manufacturing represents perhaps the largest greenfield opportunity left for digitization. As deployments increase, organizations are sometimes left seeking ways to realize immediate value from these investments.

    Many companies are now leveraging low-touch, rapidly deployable software and systems powered by the cloud like MachineMetrics that are highly accessible, quick to implement, and provide fast time to value. 

    To learn more, we interviewed MachineMetrics CEO and Co-founder Bill Bither to learn a bit more about common approaches that enable digital and IIoT initiatives, and how MachineMetrics’ Industrial IoT Platform for Machines is driving rapid and continuous value for its customers.

    MM: How is MachineMetrics enabling manufacturers to embrace the promise of industry 4.0?

    Bill: The promise of Industry 4.0, Industrial IoT, and the digital factory is to connect all manufacturing systems and assets, make sense of all of the data, and to drive action on the factory floor that increases efficiency and automation. Cisco reported last year that 76% of Industrial IoT implementations fail. This is because connecting assets requires a lot of domain knowledge and is really difficult. Projects that are scoped are just too large and cost millions of dollars. Industry 4.0 solutions are just too complicated.

    MachineMetrics has made it very easy to connect to the diverse amount of machines on the factory floor - most of our customers are able to connect to these machines themselves using inexpensive edge hardware and a web-interface hosted in the cloud on AWS. We are simplifying this process with a vertically integrated IoT Platform for Machines on the factory floor that connects and pulls data from machines, transforms this data into standard data structures. This data is analyzed and drives action through workflow triggers and out of the box applications for Factory Workers. Our end-to-end solution will connect to other factory applications like ERP/CAD/PLM/Quality to increase efficiency and automation.

    MM: With all the buzzwords surrounding industry 4.0 (industrial IoT, artificial intelligence, machine learning, predictive analytics, the edge), how do manufacturers cut through the noise and start leveraging technology to drive value today?

    Bill: The first thing manufacturers need to do is understand the business value of Industrial 4.0. Sure, the value might seem obvious, but transforming your factory from being reactive with manual systems to predictive with automated systems takes time. AI, machine learning, and the edge are just tools to achieving this objective. We must walk before we run. The first step is to identify simple use cases that leverage data. For example, by understanding equipment utilization to justify capital expenditures. MachineMetrics provides benchmarking information to help our customers understand what the industry as a whole is achieving. Another might be to close the loop on part cycle times. Changing your process to update your ERP with actual cycle times will increase estimation and quoting accuracy. For more advanced use cases, such as predictive maintenance, leveraging a platform like MachineMetrics that has studied this problem for years, and provides tools to help your data scientists and engineers build out predictive analytics that’s for your specific use cases.

    MM: Tell us a bit about how MachineMetrics is delivering solutions out-of-the-box to help manufacturers drive faster value. 

    Bill: Quick time to value is critical to success for any solution. MachineMetrics is an IoT Platform for Machines, however we wanted to be sure that our customers achieve value with out-of-the-box applications. This includes pre-configured dashboards, diagnostic tools, and an operator interface that provides prescriptive instructions to allow machine operators, even lesser skilled or newer operators, to be more efficient. We can accomplish this due to our deep domain expertise and vertical focus - MachineMetrics is focused on improving the operations of machines on the factory floor. 

    MM: How does a company go about scaling from proof of concept to production?

    Bill: Here are a few specifics I would recommend:

    • Buy-in from the factory floor through management. We have learned that having a strong internal champion can make or break an implementation. A strong champion will create alignment across the company. 
    • Establishing clear goals for the POC is important. These goals need to be achievable. 
    • Baseline current operations. Many of our customers aren’t really sure what their equipment utilization is, or MTBF prior to implementation. Having this information justifies ROI.
    • The POC should be in a production environment, just at a smaller scale, such as a single cell of machines, or one plant. Start with the expected bottleneck where the strongest ROI will be seen.
    • Integrations into other software systems or more difficult equipment should be part of the full-scale rollout, not the POC. Scaling to production or a full-plant rollout should be quite easy when this is the case.

    What are the most important measurements to consider?

    Bill: A few of the KPI's we focus in on are:

    • Cost to run and manage equipment, # of operators required, etc
    • Utilization of equipment (availability)
    • Speed of production/cycle times (performance)
    • Number of Defects (quality)
    • Unplanned downtime (machine health)

    When does it make sense to build your own solution from scratch?

    Bill: It rarely does. It’s almost always better to use a 3rd party solution because the solution provider will be dedicating itself to solving problems like yours for many companies. Even if the solution provides more than you need and you could develop the solution for cheaper - there are so many hidden costs into maintaining a solution and adapting it to changes. We have seen many companies take a build it ourselves approach only to later give up and go with us for their IoT initiative, often after spending millions of dollars in development. 

    By leveraging a platform that has APIs, there is the ability to extend and build your own solutions for problems related only to your company while still taking advantage of the out-of-the-box features that will save you time and money. This is the approach that MachineMetrics is taking - and leveraging an infrastructure provider like AWS allows for the best of both worlds. There will always be custom integrations required - for a larger manufacturer, there will likely be custom development required to connect to other systems.

    What is the right balance of depth vs breadth of services?

    Bill: Good question! A product that goes too deep might not be flexible enough for your use case. A product that is broad requires too much customization and development. Choose a platform that has specific use cases solved for your business, but also with APIs and access to data that supports extending for your own specialized use cases.

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