What do acronyms such as SFM, M2M, and HMI stand for?
Digitalization in manufacturing: an incredibly important issue, countless approaches, an overwhelming amount of information, a universe in itself. The world of digitalization is becoming increasingly inaccessible because of technical jargon that bandies abbreviations and acronyms about. This makes it difficult for newcomers to the subject. In our small glossary series, we have compiled the most common acronyms from the field of shop floor digitalization together with a "non-technical" explanation of what they mean. Part 2 of our disentanglement of terms is all about basic terms. We will be taking a look at SFM, M2M, IIoT, HMI, CNC, CAQ, and BI.
Shop Floor Management (SFM)
When managers spend most of their working hours in meetings – whether with suppliers, customers, or management colleagues – a void opens up on the shop floor. This has consequences: Employees are left to their own devices, managers increasingly lose track of day-to-day business, and the practical groundwork for good decision-making is lacking. Sooner or later, productivity and quality start to suffer.
Shop floor management (SFM) is a concept designed to tackle this. "Back to the shop floor" – or in the original words of SFM: "Leadership at the place of value creation" – that is one of the four core principles of SFM. Managers are no longer just told what is happening on the shop floor, they are directly involved. There is close cooperation between employees, a culture of leadership and direct communication are embraced, and processes are jointly monitored and improved, both continuously and systematically. In addition to this management philosophy, SFM is based on three other principles: Identify deviations, solve problems in the long term, and optimize the use of resources. These "target states" are achieved, among other things, by systematically comparing target and actual values based on standards and key performance indicators (KPIs) and by extensive visualization (of KPIs, processes, staff deployment, etc.).
Increasing digitalization therefore offers shop floor management all kinds of opportunities and scope for development. SFM tasks benefit enormously from valid, meaningfully structured, and complete data. At the same time, most shop floors that have evolved over the years (machines and equipment from different generations, manufacturers, and standards) are not prepared for this data acquisition. Hence, the current role of shop floor management is often to initiate and implement useful and feasible digitalization steps. You will find a more detailed article on shop floor management here.
Machine to Machine (M2M)
The fact that machines exchange information with each other – without human intervention – is nothing new. At the turn of the 20th century, however, in the pioneering days of machine to machine (M2M), information could only be transmitted by cable. By the end of the 1920s, however, what came to be known as "telemetry" had been developed: Radio waves made it possible to transmit measured values from a sensor to a data processing system. The technical development of telegraphy, telephony, radio, and television further advanced wireless data transmission. 100 years later, mobile communications and wireless Internet connections are creating a multitude of possibilities for M2M communication. One key application area of M2M lies in remote monitoring, remote control, and remote maintenance (which is still referred to as telemetry). Here is one example of how it is used on a day-to-day basis: A vending machine reports to a central computer that it needs to be restocked. The savings are twofold: there is no need to conduct routine inspection rounds and dwell time is minimized. Of course, the possibilities go far beyond this and similar applications – because machines are becoming more and more intelligent. This is due not least to machine learning, the artificial autonomous generation of knowledge on the basis of patterns and rules, in other words, on the basis of data. This use of M2M technology is closely related to AI (artificial intelligence) and is the foundation for the Internet of Things.
Industrial Internet of Things (IIoT)
Smart things – these are the ingenious devices that accompany us in our everyday lives, driven by the massive proliferation of smartphones. Three key ingredients are responsible for the "smartness" of things: Sensors, computer chips, and the almost limitless wireless connectivity, for example, via Wi-Fi. The combination of these ingredients has led to the development of devices that can receive, process, and transmit data, which are popular in everyday life for fitness tracking, voice control, and so on. All of these devices and services that are based on wireless connections and sensors are referred to as IoT – Internet of Things.
In addition to all the smart things aimed at consumers, there is a kind of second IoT – called IIoT: the Industrial Internet of Things. The IIoT enables direct communication between machines, products, and people to optimize manufacturing and production.
Machines are equipped with intelligent sensors and networked in order to plan processes more accurately, to better utilize equipment, to control quality, and to identify any necessary maintenance early on. The digital arm extends beyond the factory floor: In warehousing and logistics, sensors, integrated circuits, and wireless connectivity make it possible to locate inventory; the accounting department automatically receives the relevant data on incoming and outgoing goods; the HR office creates rosters based on the data records, and so on. The smart factory uses the stream of data generated by digital networking along the entire value chain. This is probably the most significant development in the manufacturing industries. You can find our detailed article on IoT, IIoT, and EoT here.
Human-Machine Interface (HMI)
Take the steering wheel in your car, or the on/off switch on your coffee machine – both are HMIs, also known as a human-machine interface or user interface. As the link between us and the respective device, interfaces enable us to operate devices: to trigger and intervene in processes. At the same time, they provide us with information (feedback). In the case of control panels, for example, this information is provided via signal lamps and display fields or via software with visualization systems. User interfaces are as old as machines themselves. And, like machines, they are becoming increasingly complex. Ever since electronic data processing (EDP) made its way onto the factory floor in the 1980s, the use of a screen and keyboard has become standard for every skilled worker. The development of the iPhone and with it, the touchscreen, is considered a revolution in the evolution of HMI. Yet following the swipe, scroll, and pinch-to-zoom features, new HMI technology is already catching on: touchless input. Most of us are already familiar with voice controls, as least in our private lives. Before long, we will also be accustomed to HMIs based on gestures and facial expressions. And yet research is already several steps ahead of that: The future of touchless technology is mind control. Headsets that measure brain waves to use them for interaction with machines already exist. They are currently used primarily to improve the daily lives of people with severe physical disabilities. For example, by enabling them to control robotic prostheses by willpower. It is therefore not unreasonable to expect that we will soon be able to communicate with Alexa, Siri, and similar devices with our minds.
Computer Numerical Control
Computer Numerical Control (CNC) Before CNC, there was NC – numerical control of machine tools using punched tape. The first computer-assisted control systems appeared on the market in the 1960s and became widely established from the mid-1970s onwards. These systems have the advantage of much faster and, above all, much more accurate positioning and movement of equipment, workpieces, and tools, which enables the rationalization of series and piece production. CNC machines work with CAM systems (computer-aided manufacturing): The system, in turn, retrieves its data from a CAD program (computer-aided design), which designs the components to be manufactured and forwards the plans to the CAM program. CNC machines are often fitted with accessories that multiply their potential applications, such as enclosures, collets, grooved plates, vacuum tables, and 3D scanners. CNC processes are used in industries such as mechanical engineering, automotive and shipbuilding, and the aerospace sector. However, practically all industrially manufactured products – or their components – come into contact with machine tools and thereby with CNC at some point during the course of their production. Having said that, numerous conventionally controlled machine tools can still be found on shop floors today.
Computer-Aided Quality (CAQ)
Always one step ahead – that is the guiding principle in the world of quality assurance. Acting in a proactive manner, rather than reacting to errors, defects, and complaints – thereby creating high process and product quality. The way forward: process optimization and production monitoring. The tool: data. This is where EDP soon came into play. Computer-assisted quality assurance has now become a central element of every quality management system. Suitable software solutions sort, analyze, document, and archive the data that supports the planning and implementation of quality assurance measures (for this purpose, the software solutions are usually modular and can therefore be adapted to a company's needs). In addition, documentation is also of central importance in the context of legal liability regulations. There is no way around a suitable CAQ solution in a manufacturing company due to the volumes of data involved and the real-time requirements.
Business Intelligence (BI)
Business intelligence (BI) is one of the major umbrella terms in digitalization and stems from business informatics. The term gained popularity in the early to mid-90s. It stands for methods and processes that companies use to collect, store, and systematically evaluate relevant data. This data can originate from within the company, but can also relate to the market environment or to customer segments (e.g., trend analyses of customer behavior). The data is used to support management decisions, for example, to check site profitability, for marketing purposes, reporting, and so on. Data collection and analysis would not in itself need to be done digitally, but in practice it is – and thus benefits both from the scale of the data that can be included, the analytical capabilities of the systems, their speed, their data visualization capabilities, and so on. BI software solutions are usually offered in modules, for example, for finance (planning, consolidation), human resources management (skills mapping, workforce planning), marketing (social media analyses, loyalty monitoring), supply chain management (delivery optimization, supplier management), sales (sales analyses), and so on.
How we approach these issues: We make sure that machines are capable of communicating with the chosen software for the relevant aims and objectives. Because this is by no means a matter of course. The problem of the "Babylonian confusion of tongues" has to be resolved (each machine/equipment speaks its own language, is manufacturer-dependent, and generation-dependent). We solve this connectivity problem. If you need us to connect your machines to your digitalization software – you can count on us.