Posthuman world — the one of the future?
This century signaled the start of our next episode in human history. In this time, we have had one amazing and unexpected journey. From the first industrial revolution (1.0) started at a large island in the north of Europe — Great Britain (XVII-XVIII) full of unbelievable inventions such as an electric telegraph (Charles and William Cooke), telephone (A. Bell 1876), industrial electric motor (N. Tesla 1888), to investing hundreds of thousands of dollars on failed software apps which could generate insanely fast-growing 7-figure businesses. Entrepreneurship is such a crazy ride that we love to follow and even I would never say I’ve seen it all but let’s just say I’ve seen a bit.
Entrepreneurship generates new opportunities and has a significant influence on economic growth. This growth can basically be attributed to fundamental indicators such as the increase in production, improvement in the efficiency of a factory and the rate of innovation. Thus, growth is driven by knowledge accumulation and innovation. Industry 4.0 is actually based on the mentioned factors. Instead of looking at just one vertical opportunity, I prefer to focus on the broader trends of autonomous machines, services and finally factories which are, generally, based on the same Artificial Intelligence (AI) technological systems. In 2017, the founder of PayPal, SpaceX and Tesla — Elon Musk, during his speeches was indicating that AI is the biggest enemy of human existence in general and people have not been prepared correctly for this change. Feng Liu, Yong Shi and Ying Liu — researchers of University of Cornell (USA), published research results in 2017, where they indicated the relations between humans and machines in the ability of the information transmission, creativity and learning skills of a few AI systems such as Google, Microsoft Bing, Baidu, and Siri. The results showed that currently we are able to build an AI system equivalent to a 7-year-old child, but actually keeping the same level of development of AI, humans can create a futuristic vision, where one day, a machine will be able to take over 100% of manufacturing processes in our factories.
Likewise, nobody likes to be replaced but the overarching goal is to get past the limits of human speed. The future of manufacture factories belongs to robots and autonomous factories. Or more accurately, belong to the post-human world.
Today’s fast-moving digital economy will reward the early movers that have already commenced their automation process with brisk movement up the learning curve. Companies which are already in the middle of this journey will be able to take over market shares easier than others and offer additional values to their current and potential customers.
Data collection & Connectivity
The industry consensus has been that we’ll continue to see, perhaps, incremental improvements in automation. But not whole businesses will switch to autonomous systems. It’ll be really tough.
An autonomous factory is something much more than robots. It’s about the entire group of different sensors and devices connected to improve the performance of a production and, of course, creating cost savings for shareholders which is one of the most important values from the business side. And the story starts here.
You are watching a Sci-Fi movie and you want to live in the same smart world. Everything around you has to be smart or even smarter than you. Otherwise, it does not make sense to keep this stuff. The same transformation is being done in industries. Devices for data collecting are being installed in many machines or entire mechanical modules. There are dozens of applications and platforms to collect data using different devices. Choosing the right solutions can, of course, save time and money for a company. A data collector is a simple sensor which monitors, collects and sends information to a central system for analyzing. What is more important, collecting data from an entire value chain can be easy but capturing the right information is a challenge. Even if companies are moving to the Internet of Things and autonomous systems, they still have a huge problem with analyzing data correctly. Big data and statistical knowledge are terms far removed from the standard interest of companies. The main data flow, based on statistics which is only a supporting process, gives an opportunity for improving the general efficiency of a company. Data collection is the first step in business process optimization. When the data flow is known, a company can identify any gaps in business processes and eventually try to predict or optimize a system. The information about data collection systems is presented in the following chart.
Data collection and connectivity are important matters for business. Data mining as a result of those fields involves analyzing data in order to identify hidden patterns and systemic relationships that can be used to predict future behaviors and help to provide a competitive advantage in business.
When we are talking about connectivity, we cannot forget about the Internet of Things. The current industries enter a new era of innovative solutions where tools such as IoT (IoT — Internet of things), based on new technologies, materials and advanced nanotechnologies, change production systems and business processes. The term IoT is not a new word. The first time it was used in the 20th century by a British man — Kevin Ashton, who as a pioneer of the technology industry, created this concept in 1999. The growing trend of production of new devices that hold sensors which communicate effectively with other devices such as computers, for instance, generates the global demand for innovative solutions. IoT is an example of the web which connects independent devices to each other, using the internet as a connector. In the beginning, the transmission was only based on one channel — machine to machine (M2M), currently, all types of devices, independent its locations, can communicate with each other using the internet (machine to machine — M2M; Machine to people — M2P; people to people — P2P). The scale of using IoT tools is unlimited: you can find them in production systems, smartphones as well as smart houses and systems such as SCADA.
Plant 4.0
Different technologies have a changing impact on human life. In general, we can indicate a technological cycle for each IT solution. Artificial intelligence, smart robots, and workspace are creating foundations for the next generation of digital business models and ecosystems. Definitely, an autonomous factory will consist of those elements, too. The only barriers are low budgets and cheap manual labor in countries such as Poland, India, and the Philippines which for many companies can be a good alternative to moving to the next stage of automation faster.
A host of emerging technologies including the aforementioned are really interesting for business. The result is a connected network or system of machines that work together. These innovative digital solutions enable differentiation through zero defect manufacturing and demand-driven supply chains. In the future, companies will seek to improve their manufacturing towards further customization and even more flexible production which will be focused on customer requirements. There are many companies which are using digitalization to make their factories more agile so they can achieve higher levels of flexibility and adapt better to changeable customer demand. More and more companies want to customize their products as much as possible. For instance, a shoe producer can create a pair of shoes for you, relying on your individual needs such as color and material. So what does a shoe producer have in common with a factory 4.0?
The main tools needed to implement solution 4.0 already exist on the global market: sensors, controllers, big data, IoT, private clouds and more other. The main difference is rather a total reorganization of the production model using current tools and placing greater reliance on the Internet and networks. Connections among machines create many opportunities and challenges for manufacturers. The basic model of an autonomous factory is shown on the following chart.
Factory of the future
The heart of a factory is one control room — a place where all production processes can be monitored and controlled and managed by employees. One control room can also improve internal communication channels because of having many different departments in one place. Apart from this, it is really a useful solution when we have to run an evacuation process.
So we can ask the question how can we actually build this digital and autonomous factory of the future? Whichever approach you decide to take, there are some aspects which are critical to ensuring a successful deployment of automation. I can indicate here the basic ones:
• Start with a proof of concept and engage the leadership team,
• Agree on operational accountability for automated processes,
• Choose a deployment model (centralized, hubs or decentralized),
• Establish automation capabilities in the organization,
• Look out for certain areas
• Manage a digital factory and workforce.
Robots or digital workforce?
Within the organization, automation also poses a series of questions that management needs to address to ensure the business has a cohesive automation strategy, and that the use of automation is optimized and does not create technology complexity which is unmanageable. Digital factories will require a new way of working and companies will need to build a digital workforce. We are entering a new era of man-machine interaction and it is critical not to underestimate the importance of people in the digital factory of the future. According to recent research, as a result of digitalization, the human employment level should stay at the same level or should be a little bit higher than today. The reason for this is the fact that new digital processes need people who will maintain the entire systems. Honestly, it should be said that the manual workforce will need to be fired or people will need to be retrained in another field. Making sure that enough workers have the right skills to support digital factories will not be easy. In general, the majority of people focus on one field their whole life without having any interdisciplinary experience combining business, economic and technical skills which will be required for doing business in the future.
According to statistics (2017), there are 74 robots for every 10,000 humans (Europe — 99, America — 84, Asia — 63, Poland — 32). Over the long term, those rates will go up rapidly. Teams must be able to solve the problem of ‘we have so much data we don’t know what to do with it’ and to tune the automation to provide a valuable and usable data set. The organization must not only be capable of mining data but to understand what problems are worth solving and how insights can be applied to adjacent problems. To enable this, organizations will need to grow their existing employee capabilities, and change the type of employee that they are looking for at recruitment.
Factory model — Project
One of the most interesting parts of this topic is a project run by people from The Advanced Remanufacturing and Technology Centre in Singapore. A public-private partnership platform created a model of a factory of the future — Model Factory@ARTC — to support the industry in their digitalization processes. The main goal of the project is to learn more about how the technologies are implemented in manufacturing use-case and test process improvements. The model factory at ARTC will feature technologies focused on heavy engineerings such as additive manufacturing and advanced robotics. With strong technical support staff, companies can verify their own ideas for improvements. Connectivity between assets and manufacturing systems deliver a lot of data for analysis and decision making. Better monitoring of utility consumption can provide the possibility of sustainable manufacturing.
In general, the system consists of three main components:
• Intelligent System and Connectivity,
• Virtual Manufacturing,
• End to End Solutions.
A “model factory” is a dashboard like in an airport control tower where all-in-one data platform analyzes real-time data from multiple machines. The following image shows a person who is taking a virtual walk across a factory.
Summary
All the right pieces have fallen into place to make AI ready to scale. The development of effective algorithms to build an autonomous factory is a key to future growth. Companies focus on vertical integration within individual factories as the main driver of their digital plant initiatives. Apart from whole digitalization, new manufacturing processes will build a new kind of workforce — a digital one. Digital factories will require a new way of working, so they will need to build or acquire new human resources. In the long term, the level of employment should stay at the same level even if companies will implement new digital solutions. Robots and AI will be the staff to improve the efficiency of manufacturing processes and build a new stage in the quality of products and services. This is self-explanatory, however, it is the most important short-term consideration to be made by companies. The longer companies wait to implement automation practices, the more time their competitors will have to get ahead of the curve, and ultimately provide more attractive and cheaper products to their customers.
Written by Lukasz Kudlak
Expert Piotr Powroznik
