Some say “smart” steelmaking has already arrived, others say not so fast. Although opinions vary regarding what actually comprises a smart mill, there is broad agreement on areas of progress and the challenges that remain.
When it comes to assessing the ground speed of any fast-moving technology, you can typically pick from any number of competing perspectives claiming to measure advances and calibrate real-world progress. Gauging the evolution and/or arrival of the smart steel mill, and, in particular, the implementation of the Internet of Things (IoT) is no exception.
Some say smart steelmaking has already arrived, others say not so fast. Although opinions vary with the definition of a smart mill, there is broad agreement on areas of progress and the challenges that remain. The smart steel mill really doesnt exist yet, says Thomas Pfatschbacher, head of technology and innovation for casting, endless strip production, rolling, mechatronics, and through-process optimization at Primetals Technologies USA. Primetals is a joint venture of Siemens, Mitsubishi Heavy Industries, and other partners.
There are new plants where people are trying many things to advance intelligence and connectivity, Pfatschbacher acknowledges. There are lots of trials and first efforts, but the fully integrated, smart steel mill does not yet exist, he insists.
That said, Pfatschbacher readily recognizes the success the industry has achieved in automating single production lines. Some examples include continuous casters, hot strip mills, and galvanizing lines, where a high level of intelligence already exists within the line, he notes. From the machine, there is connectivity and control up to operations. True automation. That also includes advanced and intelligent online and off-line models, he adds.
There are single process units with high-end automation in existence, where operators normally only get involved if something goes wrong, an unexpected process or product deviation occurs, or changes need to be made beyond those that are already built into the operating parameters (a rare occurrence in such high-end single production plants), the Primetals executive allows. This is fairly well known, for example, in modern hot strip mills, where almost all actions are fully automated he says.
But an integrated steel mill is not a single process unit, or even a series of single process units, Pfatschbacher points out. It is a combination and sequence of many interdependent, single process units, which must produce materials in the amounts and to the specifications ordered, he adds.
It is still a commodity business, where high productivity is needed, Pfatschbacher emphasizes. At the end of the day, the mill must meet customer expectations at a lower cost than that of the competition.
The challenge, then, for the smart steel mill, is to connect the process units in a way that is the optimum for the mill as a complex whole, not just for the line or unit by itself, Pfatschbacher summarizes. That connectivity and interdependence must be accomplished across the entire process from the liquid phase to the galvanizing line. Although some approaches in this direction already exist, a completely integrated smart steel mill does not yet exist, he concludes.
An advocate for process automation, Pfatschbacher nevertheless is quick to emphasize the role of human intelligence in the smart steel mill. If you look at the leading steel producers they are leaders not just because they have the best plant technology, he says. But because they have good plant technology as well as good people and systems as part of an overall operation. That includes logistics and quality control as well as operations, maintenance, product and process know-how. It is based on expertise, he says.
The pieces fall into place
The smart steel mill does fully exist, Chris Okamuro, vice president of research and development and chief technology officer at Global Shop Solutions, insists. To some degree in the U.S. there are smart elements. Most mills have implemented SCADA (supervisory control and data acquisition) systems. There has been a lot of consolidation in that space recently, he adds.
Following the money, Okamuro notes that smart sensors and the IoT to the extent it exists so far have been applied mostly to furnaces and smelters, which are being scheduled by temperature. Those units are where the energy goes so that is where the investment in smart controls has gone, he reasons.
Advances in sensor connectivity and sophistication have come at the same time as costs have come down. It is no longer necessary to have one of the big control-system manufacturers come in and charge millions of dollars to install a system, Okamuro claims. It used to cost thousands of dollars per node, and then integration costs would be 200- to 400-percent of the equipment costs. All of that is coming down, and the programming is not so specialized.
Okamuro goes on to note that the IoT as it applies to steel mills is unlikely to ever resemble the commercial IoT in the retail and consumer markets in two important aspects. Those environments are generally benign, he notes, and that communications really does take place over the Internet.
In contrast, the limits to the IoT in a smart mill are the harsh environment, he says. There is the (intense and highly variable) electromagnetic interference. There is high temperature and particulate.
Another challenge to the smart steel mill is the mind-set of management. In many cases, technology is still not seen as core to the business, Okamuro laments. But we have seen sea changes in the industry before, he allows.
We saw it in the 70s in cold and hot forming. Those changes determined who stayed around and who disappeared in the 80s and 90s, he adds. Once smart technology is available at accessible price points, the question should only be what to use.
Mike Mezler, vice president of operations for Woodlands, Texas-based Global Shop Solutions points out that often it is the mills customers that are driving change in the steel industry. Frequently they are buying automated machines. Just in the last nine months we have gotten multiple requests in other industries to read data out of machines.
Mezler suggests that a new model for shop floor operations is possible, one that takes the form of a hybrid combining full automation and human-controlled operations. There are machines now that can be programmed to run two or three jobs overnight, he points out. The operators on the afternoon shift load it up and off it goes. Things are definitely moving in that direction.
In step with that model, some jobs are performed manually or under active control during the normal daytime shifts, and smaller or more standard work is done overnight by machines acting alone.
In a joint survey conducted earlier this year by AMM and Crowe Horwath, about 30 percent of the metals companies responding said they have an IoT strategy in some stage of development and deployment. That level is in line with similar manufacturing industries.
More specifically, the survey found that companies that are closer to the ultimate customer such as fabricators, processors, and automotive suppliers are more likely to have an IoT strategy in place than those that are further removed such as producers and scrap processors. Again, that pattern matches a template typical of previous technology advances and the type of businesses which have been early adopters in the metals industry.
Overall, more than 60 percent of the survey respondents reported they do not use IoT devices at all. In those companies that do use IoT, the tools are most often employed for production control and monitoring purposes.
That would seem to suggest that manufacturers are missing opportunities to improve productivity and performance by using IoT tools available for functions such as supply chain, inventory management, and asset tracking, the survey assessment noted. That could be particularly beneficial in sub sectors where heavy materials generate significant shipping and transportation costs, which IoT technology can help manage more closely.
IoTs leading challenges, as perceived by metals companies and according to the survey, were identifying return on investment and managing implementation costs. Significantly, only a very small number of responses identified security as a leading challenge, somewhat of a surprise given the large number of high-profile, data breaches reported in recent years due to gaps in device security.
Almost all mills have some type of smart element, Mike Tomera, U.S metals leader at consultancy PwC, allows. However, it is challenging to find a mill that is entirely smart.
This is mainly because technology is advancing every day and it is difficult to continuously be on the cutting edge of the most recent breakthroughs, Tomera explains. You would have to look at the recently built facilities to find the most technologically advanced mills, he says.
Tomera noted that there are works in progress that aspire to have the most advanced, sophisticated technology available. Generally, you need to look to the recently opened mills that are leveraging technology, he says. Those are mills that were planned and built with embedded technology from the beginning and not retrofits of existing structures and mills.
The challenges relate to several factors, the PwC executive notes. The classic challenge is that of cost benefit analysis: Are the costs to implement really proven? Those can be particularly challenging in times of capital conservation in challenging markets, he adds.
Quantifying the savings is definitely possible, Tomera states. Often, the benefits are difficult to quantify when there are strides in (other important areas, such as) improving worker safety, saving lives and reducing worker injuries, or in reduced emissions.
While noting that he is not closely familiar with the smart technology specifically related to steel mills, Peter J. Scott, managing partner of private-equity firm Headwall Partners, says he has yet to encounter clients who have inquired about or ascribed value to smart technology in the context of a mergers and acquisitions transaction. M&A valuation is still largely driven by profitability, rather than technology, he adds.
Retooling or revamping?
Cyber security counts as another major cost and challenge, PwCs Tomera goes on to note. The ability to keep operations secure is a constant challenge and requires never-ending diligence, he says.
It is also important to educate operators. Workers need to be retooled to operate and maintain smart facilities, which again is a cost and a challenge (calling for decision makers) to focus on the long-term during short-term, financially challenging markets.
The general perception is that big companies have the capital, but are often reluctant to make changes while smaller companies, which are typically more nimble, may lack the financial wherewithal to fund new technology.
Tomera shares a qualified perspective. It is difficult to generalize the usage of new technology as it can be sporadic, he says. Given the need for up-front capital and ongoing upgrades, larger companies are more likely to be early adopters.
On the granular level, Primetals Pfatschbacher says that smart-sensor technology is in place. These are not just detectors to signal an alarm, but technology to trigger corrective action based on intelligent algorithms or analysis, he notes.
One indication of how extensive the Internet of Things is implemented on a mill is the manner in which deviations are treated, he explains. Todays smart sensors do more than just measure or sense; they are enablers for closed-loop control systems. The closer to the process that takes place, the lower the corrective response is in the technology hierarchy, the more automated the system can be designed.
Another common differentiator is wired versus wireless. In the harsh environment of the shop floor, however, Pfatschbacher is willing to cut everyone some slack.
More and more wireless sensors and detectors are being developed and hardened for harsh operating conditions, he observes. Still, many are wired. That is not a problem for a fixed operating environment, he says.
In short, wireless is a tool, like any other. Although there are times and locations where it is needed or makes sense, wireless is not a mandate. For a fixed sensor on a fixed piece of equipment to report by wire back to a controller or another node should not be considered evidence that the system is less sophisticated. You can deploy more antennas and repeaters, Pfatschbacher allows, but a wire can be the simplest and most reliable connection.
A larger issue is whether the IoT in a fixed facility such as a steel mill is really an internet or more correctly an intranet. IoT may not be the correct term in a mill, Pfatschbacher suggests. Maybe it would be better to call it a connected system or a local area network rather than something connected to the World Wide Web since there are still concerns about data security.
Pfatschbacher offers another possible term: the mechatronic package, which encompasses both the mechanical and the electronic and an integrated whole that includes smart algorithms and sensors. Such terminology captures and reflects the idea of keeping corrective action as local and close to the process as is safe and effective, he reasons.
Command and control
There are already machines that can monitor their own conditions like temperature and vibration and then make localized decisions depending on how serious the deviation is, Primetals Pfatschbacher points out.
In effect, the higher-level systems do not have to monitor each data point all the time, he says. The only problems that move up the chain of communication and command are those concerning process stability, safety, and quality implications. Accumulation of data continues for purposes of quality control and predictive maintenance.
If you think about the best application of smart technology in the steel mill, Pfatschbacher postulates, it accounts for the needs of the customers for certain quantities and qualities that vary from time to time and customer to customer, and balances those against the needs of the mill for operational stability, maintenance, safety, and material flows all the way back through the supply chain.
In effect the mill says to the customer, have it your way, he says. But within that, tries to keep things as close to the same way on the shop floor.
Another variable when implementing the IoT in a mill environment is whether to maintain data on site. Location and security is a big discussion, Pfatschbacher comments. Most operators want their data physically present on site, safe within their system. The steel industry is still very conservative, he says.
Sales orders may move through the Cloud or a remote data center, but operating data and process control are usually still kept close, he observes. This may change since security is not just based on local storage and the IoT can be secure.
High-end producers are having this discussion right now, Pfatschbacher notes. Mostly they feel, the data is ours, we are keeping it. But there is the need to share, at least to connect, for optimization, he points out.
Continuous optimization and monitoring require that connectivity, he adds. This could be a hurdle, but there may be and there will be some shift in thinking to the Cloud.
For all the potential of the IoT and the smart mill, structural challenges remain, Global Shop Solutions Okamuro observes. Of course, there is the mindset that if it aint broke, dont fix it, he allows. Still, there will always be some mills willing to make the expenditure for new control systems.
Even then, however, mill operators dont refit some machines more than once every few years, he notes. So, even if they are willing to invest in new smart controls, they dont have many opportunities to upgrade. That is very different from other forms of manufacturing.
Size also matters. But not in a linear way. The large mills have more ability to try more things, Mezler contends. They have the capital, the staff, and often the variety of operations.
But it is also harder to implement change at a large organization, he says. The scale is easier on the small operations, but often they make changes merely out of survival.
Another protective strategy is the local retention of data. According to Okamuro, not much of a smart steel mill is operated through Cloud-based systems because mills prefer to keep ownership of their data. There are manufacturing telemetry options, where equipment reports statistics back to the maker for quality control and maintenance, he says. But while that is possible, it is mostly kept internal.
Even in those cases, it is still possible for a company executive or plant manager to log into a Web site from a tablet device and upload operating data, he notes.