What is IoT design?

IoT products and systems combine physical and digital components that collect data from physical devices and deliver actionable, operational insights. These components include: physical devices, sensors, data extraction and secured communication, gateways, cloud servers, analytics, and dashboards.

Not only do all these components need to be designed, but their inter-dependencies must also be fully accounted for.

 

IoT Design in Manufacturing

For product and engineering teams designing IoT systems, the core challenge lies in taking IoT use cases and turning them into a connected system – with full integration, the right IoT communication protocols, security, and a user-friendly look and feel. For industrial manufacturing, IoT product design is also known as Industry 4.0 design.

 

Industry 4.0 Design Principles

There are 4 universal design principles shaping IoT design today:

four universal design principles shaping IoT design for manufacturing

1. Interoperability

At the most fundamental level, a connected system requires sensors, machines, equipment, and sites, to communicate and exchange data. Interoperability is the underlying principle throughout all Industry 4.0 design processes.

2. Information transparency

The rapid growth of connected devices means continuous bridging between the physical and digital worlds. In this context, information transparency means that physical processes should be recorded and stored virtually, creating a Digital Twin.

3. Technical assistance

A driving benefit of IoT, technical assistance refers to the ability of connected systems to provide and display data that helps people to make better operational decisions and solve issues faster. In addition, IoT-enabled things should assist people in laborious tasks to improve productivity and safety.

4. Decentralized decisions

The final principle of Industry 4.0 design is for the connected system to go beyond assisting and exchanging data, to be able to make decisions and execute requirements according to its defined logic.

 

Designing with a Purpose

In order for the Industrial IoT system to effectively fill its purpose, it must be designed with the relevant solution in mind.

Industry 4.0 Solutions

Digital twins serve a variety of solutions across the product life cycle, and must be designed to match the specific solution in question.

To give an example, a digital twin might be designed primarily for accurate, visual tracing of the root causes of machine failure, and the ability to drill down to behaviors of individual assets.

In order for an Industry 4.0 system to correctly identify the source of disruptions, it must be designed to collect data not only from OT and IT systems, but from the entire plant environment – including recipes, batch history, and other operational processes.

Without including the relevant data sets in the logical design phase, the IoT solution will fail to provide the context necessary for accurate root cause analysis.

IoT solutions must also be designed for specific end users. A predictive quality system may have different end-users than a system created primarily to monitor asset health or one which aims at predicting asset failure before it occurs. Different end users and different end goals require dramatically different approaches on the design level, from dashboard user interfaces to the data sets chosen for relevant algorithms.

Each connected systems must be designed with the specific architectures that enables it to fulfill its purpose and generate business value.

 

Transitioning to IoT Product Design

New technology layers involved in IoT design require new skill sets as well.

Almost one third of companies today lack the full resources needed to design and deliver IoT products, such as data integration know-how, web and mobile app development, data analytics, and security.

Industrial IoT Design complexitiesFaced with the skills gap, many companies source additional partners. These new, multidisciplinary teams must efficiently collaborate throughout the design process.

 

IoT Design Complexity

IoT products are a lot more complex, and with the added complexity comes the risk of making errors in design.

Throughout the design process, the costs of mistakes escalate. The result is that the later mistakes are discovered during development, the more they cost for companies.

Industrial IoT Design - the later mistakes are discovered during development, the more they cost for companies

To validate the design and ensure there are no gaps in the data flows or use cases, teams can leverage an IoT simulator. With IoT simulation, a digital prototype of the designed system allows companies to visualize system behavior and mistake-proof the logic ahead of development.

 

IoT Design Tools

Best-in-class Industrial IoT platforms provide the needed tools to support rapid and accurate logical design of IoT:

Visual Modeling

A key tool for accelerating the design process, visual IoT modeling provides a canvas to define the mechanics, electronics, data connectivity, analytics, and dashboards of the entire system.

Visual IoT modeling enables teams to seamlessly extend their CAD models – which cover mechanics and electronics – to the full IoT model, with all its added technology layers and use cases.

The Seebo Platform - Industrial IoT modeling

IoT Simulation

To quickly and easily validate the IoT system design, teams should look for a platform with IoT simulation capabilities. Here, a digital prototype is used to visualize how connected devices, edge and cloud servers, web and mobile apps interact with each other when an event is triggered, and iteratively refine the model based on the simulation runs.

The Seebo Platform - Industrial IoT modeling

Another type of simulation – IoT analytics simulation – provides teams with a means to visualize the in-market insights their IoT system will deliver, including the dashboards and alerts, taken from their model. This ensures that all needed data sources have been accounted for in the design prior to development.

 

The Physical Design of IoT

As we enter a new age in which unprecedented data is exchanged between systems, the increasing demand for connectivity solutions brings with it new requirements for product functions and capabilities.

Once companies begin the physical design of their IoT system, whether by retrofitting existing products or developing new ones, there are a host of factors they need to account for at the outset. Here, physical design means more than creating connected products, but forming an overall intelligent system.

Industrial machines, for instance, must have sensors capable of generating significantly more data than ever before, and to send the information securely for analysis and action.

Exact placement of sensors on the device, and the ability of the sensors to function in extreme conditions must be factored.

Deciding which IoT communication protocol to use for data integration is another decision companies face at the beginning of IoT design.

To simplify the complexities that arise in the physical design process, companies turn to development platforms which focus on both IoT design and IoT delivery. These platforms ensure that the physical design attributes necessary for systems to properly function and communicate, are virtually represented in the system model.

 

What is the best IoT design methodology?

There are several approaches to IoT design aimed at overcoming the challenges that IoT presents. Here we propose a combination of tactics which together accelerate and help to ensure success for the design process.

Taking a lean, agile design approach

Several product development methodologies have been adapted for efficient IoT design and delivery. The leading approach today is Stage-Gate, in which teams carry out tasks based on a detailed plan, review their outcomes, reach a gate focused on analysis, and only then move onto the next stage.

To apply this methodology of innovation to IoT design, teams can leverage visual modeling and virtual prototyping to simulate the system design, present it internally, and iterate based on feedback.

Stage-Gate product development methodology for Industrial IoT

Incorporating “Design Thinking”

The core principle of design thinking is to factor people, technology, and business into all product design decisions. This approach is customer-centric and views the customer’s needs as a crucial consideration throughout the product development process. For IoT design, this is especially important as it reinforces the notion that an IoT system is not a goal in it of itself, but rather a business solution for specific user needs.

No matter which methodology teams choose for carrying out their IoT design, if it allows for continuous review and iteration based on business requirements and customer needs, it’s on the right track.

For more information about IoT design, visit our library of free IoT resources.

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