In this second installment, he takes on the IT side of manufacturing technology with new insights into embedded software and small parts, the connected product and analytics and data management.
More than any other development, these trends underscore Smith's believe that "the age of the 'Industrial Internet' has arrived and to be successful, companies will need to change the way they do business in the future."
The saying that "parts are parts" is no longer a true statement.
The move to embed sensors in many parts to collect critical operational data is growing.
From personal experience, about 12 years ago I had the opportunity to work on a project to embed sensors in a typically mundane product -- a head gasket. The objective was to gain critical engine firing pressures and operating characteristics within the engine. The project, while it had merit, was stymied by the lack of technology we had within our "traditional" manufacturing processes. This is a typical example of why traditional parts fabricators believe that they are not ready to step up to embedding electronics and sensors into their products.
Changing the mindset of "hard parts" manufacturing from physical to software and information is a significant challenge. First, the parts manufacturer must fully understand the true operating value and characteristics of their part. For example, if their part is an axle, what are the characteristics and operating parameters that an axle provides that can be beneficial to the overall operation of the vehicle. Perhaps wheel load, torque levels and thermal conditions may be useful data that can be fed back to the vehicle to improve drivability.
Another scenario would be for an automotive air conditioning compressor. In the past, the direct driven mechanical compressor would run at some multiple of the engine speed. Today we may see an electronic inverter motor that can run at exactly the proper speed.
In order to accomplish this -- significant amounts of electronic components and embedded logic is needed.
The embedded logic is the part that can be the most challenging. In a similar process to 3-D manufacturing, the embedded logic comes directly from engineering design to manufacturing, making the intellectual properly vital.
Controlling the process from design to production is essential. If field updates are needed, the ability to provide updates online, electronically would add direct value to the end user. If that compressor needs to be placed in multiple vehicles, the programming may need to be done on the vehicle assembly line. If programming is required on the assembly line by the customer, there must be controls in place to insure quality.
One ramification for "smart parts" is the growth of royalties for embedded technology. If your company is the provider of that embedded technology, ensuring that you are getting paid properly for your technology is a concern. If you are the consumer of a product with royalties are due for use, ensuring that you are able to manage those payments is the counter perspective. In years past, even for large companies, royalty payments could be handled with spreadsheets. Today that would impose a significant effort and not be realistic in many cases.
As a company looks to create more value in their product, embedding software and sensors can provide tremendous opportunity. In addition to added value, it can also lock a customer into the technology; even if others produce the 'hard parts,' royalty value can bring added revenue. These embedded technologies will require business-operating software that can handle this new environment featuring 'smart parts', beyond scheduling for machines on the shop floor and the shipping of parts out the door.
The Connected Product
As parts become more intelligent and are able to collect and act on information provided to them, the need to enable communications from the field is becoming increasingly critical.
As an example, large engines have typically been able to collect and store operating data. This data was then read by service technicians when the engine or vehicle came in for service, providing the technician with insight into the operation of the engine.
For years, passenger cars have been equipped with onboard diagnostics (ODB2) data collection for engine and powertrain. If you ever have seen the "check engine" light on the dash come on, this is part of the ODB2 system. The engine has encountered an error, perhaps with the emission control or a spark misfire. The traditional fix would be to take the vehicle in for service where the technician will read the code and enact a repair.
As we move toward a more connected world of devices, we will see the situation where equipment will be able to call in for service and in some cases, automatically download a firmware update.
This technology has typically been used in consumer devices such as computers, high end AV hardware and copiers. These products have been 'phoning home' for years to request service. Now we are going to see this more ubiquitously.
The new hybrid from Ford will connect to the service center to download issues and request maintenance if necessary. GE's next generation of jet turbines will have enough sensors and information gathering to enable pre-diagnosis of service before the aircraft has even landed. Vehicles on the road will be communicating with one another, moving from the binary 'turn signal' type information conveyance between vehicles to more robust operating data, speed, braking and much more.
The value of gathering such data form intelligent parts and systems and then making that data available downstream to service providers is critical for the future. As a manufacturer, your customers are going to demand that your products become less autonomous and more connected. The need to have systems securely collect and manage field-produced data, then turn it into actionable value tasks is essential.
Analytics and Data Management
As a manufacturer that desires to move into the next generation, the ability to better manage large amounts of analytics is critical.
In the past, when producing machined parts that had no embedded technology, with standard scheduling of parts, working off green bar paper with a highlighter was a permissible way to handle analytics.
Today, with perhaps terabytes of data coming in from the shop floor, sensor products, products with embedded software and shop floor, systems are required that can transform this data into actionable information. Fact-based decisions are required in faster time and improved context.
Deep analytics and data management tools are now in the reach of mid-market manufacturers and no longer only available to the largest organizations. It is important that manufacturing organizations team up with the right software partners that can provide integrated systems to seamlessly collect, manage and analysis this wealth of data.
For manufacturing companies that want be a part of the next generation of the industry, the need for core business systems is critical. It is beyond just a need for software. Innovation, creativity, flexibility and agility are attributes of an ideal technology that you can work with to fulfill these needs.
The recommendation is clear -- do the research; find the partner that has a broad scope of manufacturing and expertise in these leading trends and is willing to work with you to get to the next step.
For more next-gen manufacturing trends, see part one of the series.
Warren Smith is a senior industry consultant and business strategy architect for the automotive and aftermarket industries at Infor.