By Bryan Christiansen, founder and CEO, Limble CMMS
The Internet of Things (IoT) is a network of interconnected devices that leverage data from actuators or sensors installed on physical objects or machines. Through IoT, assets can establish direct communication with humans or with each other to transfer information about their health and surroundings. In the last decade, IoT has gained rapid recognition, especially in the design engineering sector as it becomes cognizant of the importance of data and reliability engineering in developing intelligent product designs.
Disadvantages of ‘old’ data collection methods
The use of data to develop and validate engineering designs is not a new concept. It was prevalent even in the earlier design engineering practices when internet technology was not widespread. At that time, the field staff often had to go to machines to visually inspect the health and collect their data. Moreover, other data about the machine design parameters such as weather, temperature, humidity, and so on would require collection from independent stakeholders through long and tedious engagement processes. Finally, the collected data would then be compiled by the office clerk into manual registers before being sent to design and reliability engineers for future learning.
Since the entire chain of data collection was oriented around human capabilities, the data received by design engineers were often systematically biased and lacked transparency. The outcomes from this situation were quite obvious at that time – neglecting the field data altogether and developing designs based on designers’ judgments and expertise.
The impact of IoT on design engineering
IoT has transformed design engineering principles in the sense that a variety of accurate and unbiased data are readily available. Simple and cost-effective sensors or transducers can be installed that can collect parameters both internal as well as external to the machines.
For example, a pressure sensor can advise about the discharge pressure of the centrifugal pump and provide its real-time status on the cloud dashboard. The consistent retrieval of data about the discharge pressure can produce trends and provide vital insight into pump health. Similarly, other sensors such as temperature, flow, and so on can also be installed to retrieve or derive additional design parameters as they are needed during design engineering.
Currently, with the advancements of Computerized Maintenance Management Systems (CMMS) and similar software, features are available that can integrate real-time data from field sensors with the CMMS database. The merging of assets’ real-time data from IoT with their maintenance and repair history from CMMS provides invaluable insights into the overall performance of assets. The combined IoT-CMMS-driven database also provides the capability to develop predictive models that can forecast the future performance of the asset over their life cycles.
Using IoT provided data to support V&V
While the data obtained from IoT sensors can inform engineering at pretty much every stage of product development, the stage that is particularly useful is validation and verification (V&V), where machine design is cross-checked to make sure that the design complies with the technical specification.
Validation and Verifications are two distinct terms or stages and IoT-driven data can bring benefit to both. Design verification is carried at different stages of product development before the design is finalized. This is to make sure that the machine design is flowing in the right direction. The data available at the design verification stage can inform design engineers about past issues for similar machines at this stage. Since the machine design is not finalized yet, incorporating data-driven feedbacks can enable economic fixes of critical design issues which could become a major challenge at the later stages if it remains unattended.
For example, the quality of material for the design of a pressurized vessel may be verified through material endurance testing before further design of the vessel is carried out. If the IoT sensors are installed during such tests on a batch of existing in-service vessels, it can provide critical information about material performance and enable design engineers to address the relevant failure modes.
Similarly, validation is typically the final stage of product development. At this stage, the final product could be subjected to real-like operational conditions to see how the equipment behaves if deployed widely. Because most product failures occur here, IoT can be particularly useful to collect critical equipment failure data for design engineers to use to modify the product design.
How big data can strengthen continuous improvement
The process of continuous improvement is another aspect where data, in general, can be useful. Simply put, continuous improvement is the process where the feedback from different stakeholders related to the machines is systematically collected and used to improve the performance of machines during their operational lives. Some of the stakeholders would include maintenance, operations, asset managers, operational reliability engineers, and health & safety professionals.
The variety of data coming from these stakeholders are often compiled by the continuous improvement team and shared with product development and design engineering teams for improving future designs. The data collected from IoT sensors increases the level of transparency available from stakeholders and improves the design feedback process.
For example, instead of relying on a site operator to inform about machine failure, a simple and uneconomical sensor can be installed that can trigger a message on CMMS every time the machine fails. Similarly, the scripts or codes can be embedded within CMMS software that automatically and periodically generates reports of past asset failures. Such scripts can also be used to automatically suggest continuous improvement initiatives through advanced predictive algorithms. Moreover, through rapid information sharing features, the analytics and insights can be quickly disseminated to various teams engaged in similar design works thus reducing repetition of work and improving production efficiency.
The integration of IIoT with the design process
Altogether, the integration of IIoT with design has made this process more intuitive and faster in cross-functional industries. Through shared information, the connected enterprises can undertake proactive initiatives as opposed to reactive or fire-fighting strategies. While advantages are many, below are some highlighted developments that are recently happening in the IoT sector:
Edge computing: where data are stored in small centers. By storing data locally, they can be processed faster, cheaper, and in the most efficient way. Data can be made available immediately to an IIoT device, reducing the network stress and bandwidth.
Connected smart cars: Most of the advanced cars including electric cars are configurable through smartphones. The phone collects relevant information in the mobile application and transfers it to the cloud or server. From this data, manufacturers gather useful information on key vehicle parameters such as tire pressure, oil level, fuel consumption, etc. In case of an anomaly, the driver gets a message on his or her application with a recommendation to address the issue. In some smart cars, the report is also directly sent to the automobile manufacturer which can dispatch the technician directly to the user’s doorstep and also inform the vehicle engineering team about the potential failure.
Smart cities: From the context of smart cities, traffic lights are often provided with an IoT device that monitors the city’s situation. If any anomaly occurs, the system notifies the utility companies so that they can send a technician to solve the issue. This methodology is established to make the neighborhood safe, convenient, and comfortable. IoT-based street lights are widespread in major cities to record everything from the use of a shared car and traffic conditions to law-and-order enforcement.
Healthcare: By using IoT-based wearable products, the healthcare providers can gain the patient’s vital health data such as its blood pressure, heart rate, activity rate, etc. These parameters are often used by healthcare professionals to forecast patients’ health deterioration and dispatch aid in a timely fashion.
At the end of the day, accurate and timely information is crucial for the success of most projects. Design engineering ones aren’t any different. With IIoT, design engineers can have access to more data than ever, streamlining the product (re)design process.
Filed Under: IoT • IIoT • internet of things • Industry 4.0