Japan’s manufacturing industry is lagging behind in terms of the use of Supervisory Control and Data Acquisition (SCADA) system. Manufacturing Execution System (MES) and Programmable Logic Controller (PLC) are directly linked in typical Japanese factories, and as reported in the previous feature article, a factory’s operation rests on its skilled workers.

The level of understanding about SCADA among Japanese people working in production engineering remains quite limited. Some people have never heard of SCADA, and even those who know it, most think it is something to do with display/visual. In truth, SCADA has been dramatically changing its role in relation to IIoT for the past eight years. Now, SCADA should be seen as an IIoT software platform, but very few people in Japan have this understanding today.

Changing functions of SCADA

The use of SCADA in manufacturing has over an 30-year history. Until recently, SCADA had been used as a display that combines and visualizes various data of the production in the factory. The role of SCADA then was more or less limited to connect PLC made by different manufacturers, improve data throughput, enhance the speed and usability of the visual display, and clean the data for easy report preparation. 

Since around eight years ago, SCADA started to have a clear role as an IIoT software platform. In addition to its traditional functions as a display, new functions such as a tablet display (HTML5 compatible), alarm analysis, recipe management, patch process control, audit trail (management of logs) and data integrity. This special feature article provides detailed explanations of these new functions below.

Tablet display (HTML5 compatible)

In factories in Europe, it is becoming quite common that one production line for auto is equipped with more than 50 tablet devices. Whenever an error occurs, all necessary information including “what kind of error is happening now”, “who should go and fix the error”, “what kind of tools will be needed to fix the error”, “specific instructions to fix the error”, and “the extension number to the contact person in charge of the production line”. Tablet devices are distributed to all workers and/or placed in several areas throughout the factory, and thus all workers in the factory can access the same information at the same time. 

When the error is fixed, the log in terms of “by whom, how and when” is recorded. The log is used to assess the cause of the error, or if a similar or same error repeatedly occurs, the data may be used to explore the options of making more drastic changes in the production process.

Screen showing the list of extensions (source: LINX) 

Alarm analysis

Imagine a production process in which a worker must set a product part on a jig, close the cover and then press the start button. If the size of the product part is different from the specification, the cover will not properly close and even when the worker presses the start button, the process will not start. The worker may push hard to close the cover and press the button anyway, but this triggers an alarm because this is not a normal operation. 

Both major and minor alarms do happen in all kind of production processes in factories. Although the impact of one alarm may be small, altogether it has a non-negligible impact on productivity. In such a case, statistical information – “the list of alarms with a high frequency during the past xx weeks” – will be useful to consider where and how to change. The figure below shows one of such analysis.

Alarm analysis (source: LINX)

For some types of alarms, the timing (when the incident occurs) is critical for analysis. In this case, time stamp information must be recorded together with the alarm information. Some PLC’s, such as the PLC by Siemens, automatically does this by default setting, but even when such functions are not built-in, it is still possible to record the necessary data by configuring the PLC. With time stamp information, the alarm incidents can be listed chronologically and can be cross-checked with the operational status of sensors and actuators.

Collecting data and time stamp information from PLC (Source: LINX) 

When all of the data is integrated and chronologically displayed, new “findings” that are useful for the factory operations, but that have not been identified in the past can be found. There are also tools helping you to visually analyze the data and logs.

For example, you can select the specific time when the alarm was triggered and check the operation of the sensor and actuator. You will find that bulb No.1 was opening and closing at the exact time of the alarm. This information helps you identify that the strange movement of bulb No.1 is likely to have triggered the alarm.

Recipe management

Edge computing is becoming increasingly popular, but some manufacturers prefer not to keep all of the processing parameters in PLC for security concerns. Of course, preferences differ across factories, companies, and industries, but the pharmaceutical and beverage industries tend to have more emphasis on data security. For example, tank temperature is confidential information for some companies and they do not want the manufacturers of tanks or other equipment and machines to know this type of sensitive information. Also, some companies want to protect the production process from external intervention. IIoT software platform can protect the production process so that only authorized persons can conduct specific actions (e.g. change the tank temperature) and also keep the record of when, how and who did so.  

Audit trail function is built-in in IIoT software platform. So you need to have some level of authorization to change the processing parameters in the first place. And when you change the parameter, the record will be kept in a way that cannot be fabricated later on.

Patch process control

The concept is the same as that of recipe management, but patch process control refers to the idea to manage the production process through IIoT software platform. This is mainly used by the pharmaceutical and beverage industries as it allows you to change the processing parameters without disclosing key information to manufacturers of production equipment and machines. The platform, of course, has the capability to keep a record of all of the changes made.

The production process in a nutshell consists of several if-then conditional sequences. Consider a production process like this– if temperature reaches X degrees Celsius, stir it for Y hours, and then open the bulb and add Z liters of some liquid. Changing the parameter X, Y or Z is simply a change of a production parameter and it does not mean changes of the production process (if-then conditional sequences). Rather, patch process control allows you to change the production process itself, for example to something like this — stir the liquid for Y hours until it reaches temperature X, and then after T hours, open the discharge bulb and empty the tank directly from the IIoT platform without changing the PLC program.

When patch process control is used, PLC no longer has logic (if-then conditional sequences). So its function is similar to that of drives that powers actuator. The computation for conditional sequences is not done at the edge but at the higher layer connected to the Internet. As such, it may not be appropriate for application where a very quick response is needed. However, applications in the beverage and pharmaceutical industries typically have longer control cycles and in such production, patch process control is much easier to manage. It is also more secure as the log of all changes is kept. 

The demand and standard for log accuracy is increasing these days. When a hand-written memo saying “stir for three hours and put two cups of chemical into the tank” is there, you are still not 100% sure whether this is what exactly happened. Using an IIoT software platform, you can create a system that controls the work of the operators task by task. For example, a system requires the worker to press the confirmation button whenever he puts two cups of chemicals into the tank before proceeding to the next task. This prevents workers from moving on to the next task without adding the proper amount of chemicals. In other words, the production system is designed to minimize human errors.

Audit trail

Regulatory oversight by the U.S. Food and Drug Administration (FDA) and other bodies is getting more and more stringent. Japanese manufacturing, which has long been dependent on its skilled workers, faces a dilemma in terms of how to ensure compliance.

In many Japanese factories, skilled workers used to make the hand-written memo as a work log, and this had been believed to be a secure and reliable approach. The standard for security and reliability has now changed as this approach is susceptible to mistakes or fabrication. Today, the recording and keeping of all of the data automatically without human involvement is considered more secure and reliable.

Inspecting all the products (100% inspection) is the best approach to ensure product quality, but this is not realistic. Parametric release, an approach to ensure safety by showing all key parameters for production is in the pre-defined standard ranges, attracts much attention as an alternative. 

The idea is to ensure product quality by monitoring and recording all of the important parameters during the production process, rather than doing an 100% inspection. Assuming temperature is the key parameter for production, this approach records the temperature of all of the production processes and confirms that the temperature stayed within the allowed range all the time. An IIoT software platform is also good at doing this kind of management. 

Roles of SCADA are expanding significantly

As discussed above, the roles of SCADA is changing rapidly. SCADA is no longer a simple display, but an important IIoT software platform that strongly contributes to productivity enhancement.

Japan has been slow in utilizing SCADA and the use of IIoT to improve productivity is still in its infancy in Japan. Moreover, the link between IIoT and AI seems to be over emphasized in Japan. Although AI is useful in some area of IIoT, there are much more in IIoT. SCADA is one of them with a proven record of improving productivity and will be beneficial to Japan’s manufacturing industry.