Certainly, the face of modern manufacturing has changed with the arrival of Industrial Internet of Things (IIoT). This new trend is different from the smart home or wearable technologies, which are the most popular areas to employ IoT. Real-time visibility, predictive maintenance, quality control, remote monitoring, and sizeable cost savings are just a few of the benefits that adopting IIoT solutions can offer to a manufacturing facility. However, in addition to the enormous potential, IIoT technology can also pose certain challenges for software developers as they create apps for connected factories. There are five specific difficulties that stand out.
Any device that can be accessed via the Internet is at risk of being hacked. Since a lot of “things” in a factory might be connected to the Internet, it is hard to overstate the importance of information security. Your data is vulnerable to security threats both in transit and at rest as well. Many businesses today know about the legal and reputational consequences of a data loss either from the news or, sadly, from their own experiences. That is why developers should pay particular careful attention to the security issues that are related to IoT software solutions from the very beginning of the design process. By predicting, avoiding or eliminating security threats early on, you will not suffer from the pricey consequences later. Additionally, it is necessary to assess the potential need to implement advanced cyber protection initiatives to secure any enterprise networks that are already in place.
Recently, Amazon Web Services rolled out AWS Greengrass, which is a technology developed to create secure systems of connected devices that are capable of communicating with each other and the cloud even when they are offline. The ability to run tasks locally and keep device data in sync is what makes Greengrass an ideal solution to secure Industrial Internet of Things. You can read about ElifTech’s experience with AWS Greengrass here.
Due to the effects of various factors, industries continuously change over time. Additionally, the manufacturing process has evolved and continues to constantly adapt to new market demands. This shifting dynamic should be taken into account when designing and developing future software solutions for IIoT. While predicting possible future requirements is difficult and costly, engineering IIoT systems that offer improved adaptability and flexibility in mind is the obvious answer. If the system is responsive and adaptable, it will be easier for developers to add new capabilities and to make necessary changes, big or small, quickly and more cost efficiently. Given that, a significant amount of the work must focus on a careful consideration of the IIoT software architecture to ensure that it will be compatible in the future with new functionality and will integrate smoothly with the existing system.
Data Management and Storage
One device with a sensor can produce a couple of data points per second, streaming data about voltage, temperature, pressure as well as numerous other parameters. All of that information is gathered constantly and stored so that it can be analyzed later. Now, imagine a factory that has hundreds of these devices. In a short period of time, the system can receive billions of data points, which all need to be analyzed and then possibly archived. How do you manage that amount of data, and where can you store it?
There are two options. If possible, the company can purchase its own servers and store their own data locally. Alternatively, they can choose to use a cloud-based storage solution, which also allows a company to access the data remotely via the Internet. Using cloud-based platforms like AWS may be more convenient, but they can also pose security concerns. Both solutions have their own specific pros and cons, and a developer’s job is to assess the risks and benefits given a particular case to select the one that best fits the needs of the business. Customers are rarely tech-savvy, so a good programmer should consult with the clients to assist them to identify which solution is the best option for them.
There’s no need to say that thorough testing is an integral part of any software development process, right? Still, often companies that are looking to adopt IIoT software solutions need the solutions operational immediately, so they compromise on quality assurance. In another scenario, the development takes up most of the estimated time, and there is simply no time remaining for testing. That is why a qualified software engineer has to consider any major inefficiencies and/or bottlenecks that might occur in the system to tackle them early on in the development process to minimize the length of testing required and potential delays later. For example, software engineers should check whether a system will work properly given the factory’s particular configuration, which is a challenging task that requires recreating an almost identical factory environment. It is up to the software developer to recognize the possible weak points and potential pitfalls of the system even prior to testing or in the worse-case scenario without any testing at all before implementation.
Lack of Standards
We all know that Android and iOS are the mainstream standards for smartphones and tablets. IoT, unfortunately, cannot boast this level of standardization. The lack of a standard platform-based approach in IIoT is a significant challenge for developers since it results in most of the software being created from scratch. This is good for personalization but bad in terms of quality assurance as well as efficiency of time and money. Not to mention that different systems “speak” different languages, which means that making them interact is no piece of cake. Solving security, interoperability, and numerous other problems as well as creating a common architecture would be so much easier with unified standards and protocols.
Industrial IoT differs from its more consumer-based counterparts in terms of system volume and complexity, which imposes additional challenges on the development of software solutions for IIoT. However, creating apps that turn a regular factory into a smart one only solves half of the problem. Adjusting factories’ legacy equipment to work properly with progressive software can also be costly and challenging. Furthermore, companies need to set up regular trainings for their staff to teach them to successfully complete their jobs within the new system, to understand the insights that the data provides, and to apply this newly acquired information for further optimization. Creating a smart factory requires a complex approach; otherwise, you risk investing a lot of time and money for little to no value-add in return.
If you’ve decided that your manufacturing facility needs to become connected, make sure that you find the right partner to assist you to make your plan reality. ElifTech is well-versed in how factories can make the most out of implementing IIoT technologies. Our experienced software engineers create innovative IoT solutions that benefit manufacturers. Contact ElifTech, and start making a factory of the future today.