Making the Intelligent Factory Today

Part II: Making the Intelligent Factory Today

What are the tools and techniques you can apply right now to begin reaping the benefits of the industrial Internet of Things (IOT)?

With relentless buzz around the industrial Internet of Things (IIoT), it’s easy to dismiss it as hype. The reality is that factory intelligence can streamline operations, boost overall equipment effectiveness (OEE), and increase profitability. By converting performance data harvested from the equipment into easily consumable information and putting it in the hands of staff up and down the food chain, factory intelligence enables manufacturers to build better product faster and more cheaply.

Consider a bakery in the middle of a run of frosted holiday cakes for a box retailer. It’s a huge job with a substantial penalty for late delivery. The line is busily operating 24/7, turning out dozen cakes a minute with complicated decoration when the drive for a set of servo motors that applies fluted spirals of frosting begins registering a higher current draw on one of its motors. The cakes aren’t swiveling at the proper intervals, the frosting goes on incorrectly, and the waste at the end of the line increases.

The drive alerts maintenance that there is a problem but also sends notification to the floor manager and plant manager so that they’re aware of the decrease in output. The engineering team is dispatched to fix what turns out to be a failing bearing. Even as the line stops for the repair, management on the top floor checks capacity at a plant in a neighboring state to ensure that the company can act as backup if the line is down longer than anticipated. At the other bakery, the manager accesses inventory information to ensure that it’s able to produce the necessary cakes and properly package them. The bakery has a solution and a backup plan to ensure that the customer gets their cakes. Disaster averted.

The state of factory intelligence
Intelligent components with machine-level connectivity is nothing new. In today’s market, gathering data and exporting it to the ERP system for off-line batch analysis is commonplace. It can be useful for business analytics, operational assessments, and even long-term performance and diagnostic evaluation (think modeling for preventive maintenance). What is new and still emerging is the IIoT approach – capturing detailed data in real time, analyzing it and putting it in the hands of staff up and down the food chain who are in a position to act upon it.

Practical applications include monitoring work in process or doing lot and batch tracking to enable end-users to better manage quality control and recall analysis. In the food and beverage industry, the technology manufacturers apply the technology to improve production capacity, more effectively monitor all materials in the production process, and understand asset utilization. As shown in the example above, when orders come in from the production scheduling environment, the visibility equips staff to immediately identify available capacity so that they can move production to those assets to meet targets, whether they are cross the country or on the other side of the world.

Another straightforward route to savings is through energy management. Energy represents one of the biggest costs in manufacturing. It’s not simply a matter of overall consumption but the nature of that consumption – price varies by time of day and gets rescaled monthly or quarterly by the peak usage of the previous term. Being able to monitor energy consumption as it’s happening allows end-users to schedule energy-intensive tasks during off-peak hours. They can also spread out high-energy activities to minimize their peak energy consumption.

Factory connectivity makes it possible to efficiently monitor the condition of assets. More than one company with a production shortfall has started to invest in a new machine only to discover that the reason they are not making enough product is because their current equipment is no longer running to spec. Traceability enables operators, maintenance, and managers to  easily monitor output to keep all assets operating as close to design levels as possible.

It also helps eliminate unexpected downtime. Think predictive rather than preventive maintenance – if the temperature of the cake oven in the previous example begins to drift, perhaps because of a failing thermocouple, the controller can adjust conveyor speed and also alert the controls team and maintenance so that they can respond before the oven begins burning product. Moving from a preventative to predictive maintenance regime not only reduces costs from downtime, it optimizes capital investment. Organizations are no longer replacing perfectly good components simply because the calendar and statistical analysis say they should.

Have a Plan
This is just a sampling of the benefits to be had from factory intelligence. The challenge is how to implement the technology. The smart components that form the backbone of the smart factory are probably already installed in your equipment. How do you connect them reliably and securely? How do you get the data from the shop floor to the users up and down the food chain, and most important of all, how do you convert it from bits and bytes into actionable insights?

For starters, have a plan. Psychological studies have shown that people who articulate their goal are more likely to achieve it. Know before you start what you want to do, and make sure it’s achievable. Start small and with success, build outward. Gathering data simply because you can is the surest path to frustration – and failure. Data isn’t free. Acquisition requires hardware and software and time, as does analysis. Memory might be cheap these days, but in volume it adds up and consumes power and space. Meanwhile, trying to complete too many things at once may mean that you accomplish nothing at all.

A better approach is to identify a particular problem – a pain point, a business risk you wish to protect against. Identify strategy to use intelligence and connectivity to address that problem. The investment will be smaller and the scope of the problem easier – and faster – to address. Once you succeed, you can look for new targets, and you will likely discover that you have an easier time making the cost argument for additional hardware and software to support more ambitious goals.

Gather the Data
Once you understand what it is you’re attempting to accomplish, you can make the right choice about monitoring and data acquisition. Many if not most modern PLCs have some data logging capabilities. For a machine or process with limited data capture needs, the smart HMI with data logging capabilities may get the job done nicely. For a pharmaceutical application that requires absolute traceability for every product throughout manufacturing and packaging, a dedicated data logger may appear required to handle the flood of data, making it available for immediate use, and storing it for easy access. As in all things in engineering, the fine points of the application of determine the best solution.

Make the Connection
So you’ve defined your problem and installed the correct hardware to monitor the parameters of interest. The next task is to move that data to where it is needed, whether that is the enterprise resource planning (ERP) system for enterprise-level analytics and scheduling, the supervisory control and data acquisition (SCADA) software, or the manufacturing execution system (MES), to evaluate and optimize production. The levels of functionality among these three layers varies so broadly, as do the needs of any one organization that an effective factory visibility solution may consist of one, two, or all three. In any case, the connectivity layer installed to pass data from the machine layer up to the various monitoring and analytics systems should provide secure, fast, resilient bidirectional communications.

Historically, that task has been performed by a gateway PC. It’s a good fit for complex, data-intensive applications. On the downside, these interfaces have traditionally set the stage for conflict between the IT department and shop floor operations. The IT shop is reluctant to give up information about the enterprise network to configure the device, while the plant floor doesn’t want to allow the IT shop to have access to their machine controls. Another problem manifests over time. IT platforms change and upgrade on a regular basis. If the interface involves custom code, then work may need to be repeated at regular intervals.

Alternatively, it may be possible to use a dedicated interface device that passes information directly from the PLC to the database that feeds the MES/ERP system. Known as edge devices, these interface appliances can bridge that gap between the IT shop in the shop floor. The IT department can configure its side of the appliance while the shop floor staff configures its side. For the right application, it can be faster, easier, and more cost effective than the gateway approach.

What layers are you connecting?
In some cases, monitoring drives or energy consumption may be enough. For applications like medical and pharmaceutical, or for manufacturing organizations working to gain a competitive advantage, the next step is working with product lifecycle management suites. The goal of these cases is full visibility of a product from the design phases on through volume manufacturing. It might link and trade data among CAD, CAM, and mechatronic solutions with the manufacturing and enterprise-level software we’ve been discussing. It’s a much more ambitious goal than has been discussed so far, but it doesn’t have to be difficult added as part of an ongoing strategy. It can also simplify meeting regulatory requirements for approval and production of high reliability devices like medical, automotive, aerospace, etc.

Given all the above, it can still seem intimidating to begin implementing some of these techniques. The good news is that the products discussed here are available on the market. The even better news is that most are designed for ease of integration and shortest possible time to value. Automation suppliers are in an interesting position in that they use their equipment to make their equipment. They recognized the need for factory visibility early on and begin developing their own in-house solutions. Now, several are making those solutions available to customers.

Acknowledgments
The input and insights of the following people were indispensable to the completion of this project:
Michael Cromheecke, Rockwell Automation; Daniel Martinez, Siemens Industry; Corey Morton, B&R Industrial Automation; Beth Parkinson, Rockwell Automation; and Sloan Zupan, Mitsubishi Electric Automation.
 

Part II: Making the Intelligent Factory Today