Goals and Issues when Implementing the Industrial Internet of Things (IIoT) in Factories of All Sizes
There have been efforts to promote digital transformation (DX) in a number of countries, with examples including the announcement in 2011 by the German government of Industry 4.0 (the Fourth Industrial Revolution) (approved in 2012)*1 and the initial proposal by the Japanese government in 2016 of Society 5.0*2 as part of its 5th Science and Technology Basic Plan. It has therefore been some time since the expression Industrial Internet of Things (IIoT) started spreading and eventually became established, and there has been a great deal of discussion related to Industry 5.0 (the Fifth Industrial Revolution). Against this background, the concept of IIoT has begun to shift from one centered around things to one centered around people, and a large number of solutions and use cases have emerged with the aim of providing a more sophisticated user experience (UX).
The common thread is that they are all undeniably useful means of boosting the efficiency of operations and increasing productivity, such as by accumulating data and putting it to use in the monitoring and management of the production process or operating status, or in trend analysis, predictive maintenance, and identification of improvement tasks. Nevertheless, regardless of the scale of the company or factory, it is not always easy to find the ideal solutions for deploying IIoT in all processes.
Reasons for this include cases where implementing factory automation, the most representative change associated with the Third Industrial Revolution, and the associated in-line data collection, is difficult due to the characteristics of particular processes or how they differ from other processes. It is therefore not surprising that the idea has taken hold that implementing a smart factory utilizing IIoT, the symbol of the Fourth Industrial Revolution, is not an easy task.
Today problems or bottlenecks deploying IIoT have emerged alongside diverse solutions and services. Below we introduce ways to choose smart IIoT implementation methods that solve earlier problems or issues and provide some related hints.
Examples of Problems or Bottlenecks Implementing IIoT
We will review as typical problems or bottlenecks implementing IIoT, processes involving human workers, securing DX personnel, affinity with environment and conditions, and concerns regarding overabundance of options, costs, and effectiveness. In the discussion that follows we introduce representative examples of each.
Processes Involving Human Workers
Some processes simply require the involvement of human workers to perform mechanical operations, use of tools, or manual labor, and this can mean that tasks such as moving work between processes or performing inspections can only be performed off-line by human personnel. Also, depending on the product, autonomation may be difficult with current technology, and there are cases where meticulous, delicate tasks performed by human workers are required in almost all processes.
In cases such as these, management of uptime and identification of problems and improvements based on data acquisition and visualization of conditions, as well as analysis, are difficult, and often reasons such as this can impede the deployment of IIoT.
Securing DX Personnel
Knowledge and expertise related to Information and Communication Technology (ICT) are essential in order to construct IIoT devices and systems in factories for transferring and storing data in such a way as to ensure that they operate stably and as intended, and in order for IIoT to be useful for improving operations by making use of collected data for visualization and analysis. However, securing DX personnel with such knowledge and expertise can often present a bottleneck for the manufacturing site. What’s more, there are sometimes cases where even if an IIoT solution is deployed, it is not possible to obtain the desired results from the collected data. There are probably not a few factories where fears that support may not be available from persons with specialized knowledge present a hurdle to the implementation of IIoT.
Affinity with Environment and Conditions
In most cases, the implementation of IIoT requires the autonomation of the various processes, of course, as well as a network system to control and manage them. No matter the size of the factory, there may be some processes that use machinery and equipment that cannot connect to the network or are unable to input and output data, or where operations involving human workers account for a large share of the total. This can mean that the network system is incomplete or was not constructed in the first place.
Also, even if a network system was constructed, a variety of concerns, such as that the complexity of wiring to provide power and wired communication links to IIoT devices such as sensors will increase the workload when rearranging or replacing equipment, or that using wireless links will result in signal interference, can prove worrisome when considering IIoT deployment.
Finally, with regard to network security, there may be limitations or restrictions on the use of cloud-based services operated by third parties due to security-related agreements with corporate clients or in-house rules.
Concerns Regarding Overabundance of Options, Costs, and Effectiveness
Today there is such an abundance of IIoT solutions and services on the market that it can be difficult to decide which of the available options are the best fit for one’s own factory.
In addition to the initial deployment costs, we cannot ignore as additional factors increasing the difficulty of IIoT adoption considerations about running costs, such as the usage fees for cloud services, concerns about whether or not the solutions chosen will be a good fit for the worksite and target processes, and uncertainty as to whether they will work as intended.
The New Age of Making a Small Start in IIoT Deployment that Can Be Supplemented Later
As stated above, the IIoT concept has taken root in the marketplace, and a wide variety of IIoT devices, solutions, and services are available for purchase. Businesses can choose the options that best meet their needs and deploy them. Solutions are also emerging that enable “small start” IIoT implementation of processes that previously would have been considered too difficult and to supplement partially incomplete implementations.
As the term implies, making a “small start” means beginning with deployment on a small scale by starting with the operations of a specific process or set of machinery or equipment. This approach provides the major advantage of making it easy to implement a “proof of concept” to determine if the desired results can be achieved in cases where deploying a large-scale system would be too difficult. In addition, it avoids the substantial initial cost of deploying a large-scale system all at once and minimizes risks associated with whether or not the solution is a good fit and the possibility that the running cost may exceed the benefits achieved. Making a small start is a good way to gain knowledge and experience, and expertise of IIoT by starting on a modest scale.
What’s more, this sort of solution may also be appropriate in cases where IIoT has been deployed to most of the factory, allowing IIoT solutions to be implemented in particular processes where digitization and visualization have not yet been realized, such as those involving human workers. Scaling up in this way makes it possible to make up for gaps in data collection.
How to Select Solutions for Making a Small Start or Scaling up IIoT and Related Hints
Below, we present advice and hints on how to select solutions for making a small start to get around issues that previously prevented IIoT deployment or to scale up by supplementing areas that were lagging behind.
Collecting Data without Autonomation of Processes
Previously, it was typical to install IIoT devices such as sensors in-line as part of factory automation, to collect and store data, and to use it for monitoring, visualization, analysis, and the like. However, now there are ways to introduce, even into off-line processes involving human workers, IIoT devices that can subsequently be installed to allow the collection and utilization of data.
For example, DX can be easily achieved for each process or task using solutions that just require operators to perform simple and intuitive operations such as pressing buttons or moving small devices, or simple manipulations using tablets or other input devices, in order to gather uptime or progress data that can be used to identify problems and make improvements under the 3M (Muri, Muda, Mura) concept associated with the Toyota Production System. The important thing is to select IIoT solutions that minimize the burden on operators and the effect on takt time.
Availability of Specialized Support from Deployment through Operation
Securing DX personnel with specialized knowledge is an important issue at the manufacturing site. Simply purchasing IIoT devices and purchasing or leasing software for analyzing the data they collect may not be sufficient to ensure that the system operates as intended and the data can be utilized fully.
Even in the case of a small start, to avoid spending too much on the initial investment and running costs it is important to obtain attentive consultation before deployment and support afterwards from personnel having specialized knowledge.
Using Wireless Devices to Avoid Complex Wiring
Considering the complexity of wiring to provide power and communication cabling to IIoT devices such as sensors, the increased workload when installing, rearranging, or replacing equipment can present a barrier to deployment.
With this in mind, one option that should be considered is IIoT devices such as sensors with support for wireless communication. Many such devices are available in rechargeable versions with extended battery life, eliminating the need both for power cables and wired communication links. What’s more, many such sensors can easily be mounted afterwards on equipment that is already in use.
Nevertheless, even though IIoT devices supporting wireless communication are available, data transfer may be unstable in factory layouts containing large numbers of obstacles, such as machinery and equipment. Selecting devices that support the sub-GHz band, which is less affected by obstacles, may be a solution for ensuring stable communication and operation in such environments. Sub-GHz networking allows you to select wireless devices that are very power-efficient and therefore offer extended battery life, effectively killing two birds with one stone.
Making a Small Start with Specifications and Costs Matching the Goals and Environment
Making a small start with IIoT can have a high level of difficulty when it involves your company independently constructing a system consisting not only of devices such as sensors of various types, but also combining them with gateways, software, and your own premises, as well as cloud services, etc., with their own running costs. Also, the requirements of the system that needs to be constructed to match your goals will differ significantly based on questions such as whether to use sensing to monitor machinery and equipment or whether to digitize and collect data on operation uptime.
Selecting solutions that are easy to adapt to your goals and environment will simplify the process of making a small start. These include not only IIoT devices but also devices that include software that simply needs to be installed on your company’s PCs to enable visualization of data and that can easily be configured to meet your needs.
Another important basis for making a selection is whether it is possible to conduct a trial before full-scale deployment to confirm that a solution matches your goals and environment. Implementing a proof of concept beforehand enables you to avoid excess costs.
Summary: Key Points when Selecting an IIoT Solution
We have described some of the problems or bottlenecks faced by factories that have not yet begun to implement IIoT or have deployed it only partially, and we have explained how to select solutions for making a small start at IIoT and provided some related hints. In closing, we will list some key points to guide you toward a successful small start at IIoT deployment or scaling up of an existing implementation.
Affinity with Processes Involving Human Workers
When used to collect and analyze data on worker operating time, will the IIoT devices you are considering be easy for operators to configure and operate, not impose a burden on managers, and have minimal impact on takt time?
Availability of Support and Ability to Conduct a Trial
Is specialized support available from the pre-deployment stage through operation at the actual manufacturing site? Also, is it possible to conduct a trial before full-scale deployment?
Wireless Communication and Battery Life
Will you be able to avoid complex equipment setup associated with power and communication cabling for the IIoT devices? Also, in settings where physical barriers or the like might impede communication signals, make sure to look into devices supporting the sub-GHz band as a way to achieve both stable communication and extended battery life through power efficiency.
Support System for Easy Deployment
Is specialized support available from the manufacturers or publishers supplying the IIoT devices such as sensors and the software, etc., for visualizing and analyzing the data collected by them to enable you to smoothly deploy and operate a setup matched to your company, including costs?