The Challenge of IoT: Engineering M2M Communications

Each day, the media publishes new stories about the Internet of Things (IoT), often focusing on the promises and perils of enabling machines to communicate autonomously with other machines. While many of these stories look at self-acting or remotely hacked machines posing a threat to humans, the IoT story not often told is about how machines – equipped with sensors, programmed (by humans) with rules – can effectively communicate specific sets of data to other machines, which in turn use the data to efficiently, precisely, and safely perform certain crucial steps. The idea is to advance what we know as machine-to-machine (M2M) communications, by creating a network of self-monitoring, adaptive learning machines with the capacity to generate and transmit data – in real-time – in ways that offer immediate, complex interoperability designed to serve specific human requirements.

Achieving this level of integrated performance, however, is quite distant from the examples we mostly see today. Presently, much of the IoT discussion is happening in the consumer space, where IoT is discussed in relation to how devices provide conveniences that make our daily tasks easier: If we want to change the channel on our TV, or switch to another radio station, or adjust the brightness of your lights or the temperature in the room, you can simply press a button on, for example, a mobile device. This level of connectivity is about remote functionality rather than M2M integration.

The significant possibilities emerge when we think about IoT in relation to machines which learn from our behavior and their own environment. One example is the NEST thermostat. However, its capacity to detect and process input about human preferences, and then use this information to predict a building’s interior temperature, is only a glimpse of what we can achieve. To take this connectivity to the next level, consider this possibility: Each weekday you typically arrive home at 6:00 pm, and your NEST thermostat knows this and responds by heating your home so that when you arrive at 6:00 pm, the interior reaches the right temperature you desire. But then one day, while driving home from the office, you encounter travel delays resulting from traffic congestion, which causes you to run about 20 minutes later than usual. Your car’s system detects this delay, calculates its impact, and then transmits a new arrival time to the thermostat, which responds by reprogramming itself so that it syncs its operation – of preheating/precooling to the desired temperature – with your expected arrival time as well as current and forecast weather conditions. The result is less energy used in the home, which translates into lower energy costs for you. This type of scenario, especially on a larger scale of entire buildings and cities, is where we start to see significant benefits from embedding smart connectivity into machines. This is when IoT becomes part of an overarching strategy for improving long-term cost performance, resource allocation, and overall convenience.

Presently in industrial environments, there is little M2M communications. What we mostly have today are machines that require humans to complete a single, repetitive task. An analogy is a football team: If the players on the field fail to communicate, each is acting in isolation, and together they will not reach their goal: winning the game. Transpose this analogy to an industrial setting, and you have machines and robots in a factory today that are not talking, and the data which these machines generate stays local to each machine. This non-integrated system lacks the flexibility to perform high-value tasks as needed. For manufacturers, not enabling machines to communicate is a missed opportunity to coordinate production activity. From this type of failure comes redundant processes, frequent downtimes for changeovers, and machines running when not needed.

In the smart factory, the machines and robots are equipped with the technology – hardware and software – that enable M2M communication and interoperability. This technology facilitates the transfer of data in one machine to other machines in the same factory – as well as to the infrastructure and to users connected through the Internet, through all types of other devices, such as smartphones and smart garments. Through this transfer – this smart connectivity, machines generate raw data, communicate it to other machines (as well as to networks and clouds), and then through techniques such as Big Data analytics, process it into real-time visualizations of production. From this information, machines can autonomously make decisions about possible actions – within the parameters of specific patterns and rules (which engineers program into the machine’s operating system) tailored to achieve certain types of operational efficiency improvements, such as shifting into pause mode immediately after it completes a production task, as a way to reduce energy use. These rules and patterns also enable unprecedented flexibility in production.

From a top-level view in factories, everything is controlled by consumers. And as consumers, we all want each new version of a product to be better, faster, cheaper, and more efficient – and we want more customization to our individual preferences and requirements, because each of us wants to express ourselves as individuals within our mass-production world. The MINI passenger car is a prime example of such customization,  customers can select from among a diverse range of available options to build what they believe is a unique vehicle, one that they helped create and which represents their individuality. Getting this level of customization in mass production requires a completely new approach to production. To do this, we need something like batch size one, which is the ultimate aspiration – and not impossible for things such as unique mobile phones. Reaching this point successfully and affordably requires first-time-right approach to production, where IoT-enabled M2M communications could be the enabler. Without this approach, achieving customization with current production approaches makes the cost of a unique mobile phone very high.

Despite the hype and hyperbole common to most discussions about IoT, there is increasing recognition about the potential significant ROI which manufacturers can generate from smart connectivity. This is the key to helping a manufacturer turn a conventional factory into a smart – or connected – factory. To get there, senior leaders need realistic snapshots of the success which can be achieved, and they need to understand how IoT can directly result in significant production increases and waste reductions. To satisfy these information needs, engineers need to first answer a crucial question when making a case for IoT investments: Is expected performance improvement a direct result of IoT – or will IoT only make improvements easier? To answer this, build a case around the three benefits of investing in IoT.

Over the next few years, there will come a point when manufacturers will need to invest in IoT technology. To get there, the engineering community needs to communicate individual successes to each other, to organizations, and to the larger business community. Presently in Germany, Industrie 4.0 – the Industrial IoT – is perceived as the fourth revolution of industrial life. Which calls to mind the story of Henry Ford. When Mr. Ford started, he was competing with the horse-and-carriage, and there were many people who were saying that the automobile would never replace the horse-and-carriage, which was the then-standard form of daily travel. But as we now know, that standard way of doing things was replaced with a new better way to travel and to think about travel.