Manufacturing Economy

The full article was originally published by Daniel Trauth on Medium. Read the full article here.

Preamble

This article is based on the Ph.D defense held by Anton Shirobokov. Anton worked with the WZL for approximately 6 years before undertaking a new challenging role with Robert Bosch GmbH in June 2018.


Abstract

The possibilities and challenges of the Industrial Internet of Things have been investigated for years at the Laboratory for Machine Tools and Production Engineering WZL of RWTH Aachen University under the topic of Internet of Production (IoP). The IoP focuses on interdisciplinary optimization approaches along with the entire value chain, especially in the areas of data acquisition, machine learning and artificial intelligence. This article evaluates whether and how the vision of IoP can be extended to a Manufacturing Economy. Distributed ledgers in general, and IOTA in particular, were examined for this purpose. Subsequently, IoP potential use cases for the area of manufacturing technologies were outlined, but it turned out to have greater potential in manufacturing economy.


“Digital is the main reason just over half of the companies on the Fortune 500 have disappeared since year 2000.”

— Pierre Nanterme, CEO of Accenture


1. Introduction

The Industrial Revolution is a rapid and dramatic social-economic change caused by the adaptation of a new technology [GEHR15]. Industrial revolutions are rapid developments that bring about dramatic change. The First Industrial Revolution shifted society from an agricultural to an industrial model with advances in transport and early mechanization by steam power. That was the beginning of the machine work, see Fig. 1.

Fig. 1: Industrial development through the perspective of revolutions [GEHR15]. Image: © WZL | Anton Shirobokov

The Second Industrial Revolution took us one step further: electricity has enabled mass production of cars, railways and telegraphs, which opened the age of mobility. The Third Industrial Revolution introduced digitization through the invention of the computer and the internet. These inventions help in connecting people and value chains. It has brought a new level of efficiency and automation which is transforming several economic sectors, displacing powerful established companies and overthrowing established business models.

The convergence of new technologies is accelerating so fast and we don’t want to miss the opportunities it brings. Today we are on the verge of the Fourth Industrial Revolution — combining the physical (from the first and second industrial revolution) and the digital (from the third industrial revolution). Identical to the previous industrial revolutions, machines will also play a dominant role. The key difference is that they are now becoming smart but not yet at self-awareness level.

(Industrial) Internet of things

The Internet of Things is the network of all physical devices and systems that are connected to the Internet. It enables interaction and data exchange between devices and people. The IoT market has grown significantly in the past and will continue to grow exponentially in the future. Recent studies assume that by 2025 every person will have about 10 to 12 connected devices [STAT18]. Smart cities and the industrial IoT sector are the main drivers of the IoT market with a market capitalization of around USD 267 billion in 2020, see Fig. 2.

Fig. 2: Growth and market capitalization of the Industrial Internet of Things market [STAT18]. Image: © WZL | Anton Shirobokov

Internet of Production

A direct application of the IIoT approach to production engineering is currently not sufficiently feasible, as there are many more parameters, but much less available data compared to other big data application domains. Modern production is characterized by vast amounts of data. However, this data is neither easily accessible, interpretative, nor connected to gain knowledge. With the Internet of Production (IoP) the WZL and RWTH have the objective to enable a new level of cross-domain collaboration by providing semantically adequate and context-aware data from production, development and usage in real-time on an appropriate level of granularity. The central scientific approach is the introduction of Digital Shadows as purpose-driven, aggregated, multi-perspective and persistent datasets. The Cluster of Excellence (CoE) will design and implement a conceptual reference infrastructure for the Internet of Production that enables the generation and application of Digital Shadows. For the realization of the IoP, Aachen’s highly renown researchers in production engineering, computer science, materials engineering and further necessary disciplines team-up to solve interdisciplinary challenges, like the integration of reduced production engineering models into data driven machine learning for cross-domain knowledge generation and context-adaptive action. The IoP will be leveraged by the production engineers in order to support a new way of more holistic working on — and with — systems by developing and advancing engineering tools, methods and processes. Therefore, an integrated development for the entire production technology is required.

Fig. 2b: The Vision of the Internet of Production. Image: © WZL

Machine Economy

In a machine economy, self-monitoring and autonomous machines, devices and systems will be able to order services such as maintenance, organize their own production and make decisions with the trust of their owners [RAJA17]. These services are initially provided jointly with people, but increasingly also by other machines, see Fig. 3.

Fig. 3: The definition of the machine economy and its long-term effects [RAJA17]. Image: © WZL | Anton Shirobokov

Industrial companies will try to avoid on buying expensive equipment and machinery, instead there will be a kind of Uber-isation of self-managed assets that share their services in a decentralized ecosystem. Machine subscription models and real-time leasing will be widespread. Machines are increasingly becoming independent market participants and independent financial actors with their own bank accounts and payment systems. These machines will be built to avoid inconvenient human interaction in turn of creating new challenging fields for people in this new market.

Six pillars define a machine economy, see Fig. 4: Machines and systems must be digitized with the aid of sensors that make machine states visible and enable machine-to-machine (M2M) communication in both directions, transmission and reception. With the help of artificial intelligence, these machines can work alone in a decentralized sharing economy in which the operators no longer define value through ownership [RÜTH17]. The backbone of such a machine economy is any distributed ledger technology that enables trustworthy data exchange and smart contracts between the devices.

Fig. 4: Pillars of machine economy [RÜTH17]. Image: © WZL | Anton Shirobokov

Intermediate conclusion: Introduction and Machine Economy

  • Smart, connected, and autonomous cyber-physical systems emerge as a result of the fourth industrial revolution
  • Autonomous machine-to-machine (M2M) transactions give a rise to the machine economy
  • Data is a major resource in the machine economy: data is the new oil
  • Distributed ledger technology (DLT) is the data backbone of the machine economy

Read the full Article

The full article was originally published by Daniel Trauth on Medium, where people are continuing the conversation by highlighting and responding to this story.

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