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This publication examines the opportunities and challenges, for business and government, associated with technologies bringing about the “next production revolution”. These include a variety of digital technologies (e.g. the Internet of Things and advanced robotics), industrial biotechnology, 3D printing, new materials and nanotechnology. Some of these technologies are already used in production, while others will be available in the near future. All are developing rapidly. As these technologies transform the production and the distribution of goods and services, they will have far-reaching consequences for productivity, skills, income distribution, well-being and the environment. The more that governments and firms understand how production could develop in the near future, the better placed they will be to address the risks and reap the benefits.

Foresight can be a highly useful tool to address the opportunities and challenges triggered by the next production revolution. As shown by the various country cases considered in this chapter, foresight facilitates debate and systemic thinking about multiple futures and helps to shape the future through processes of participation and engagement. Given its participatory nature, key actors are mobilised to form shared views about the future, negotiate their future stakes and interests, and agree on actions aligned with their shared vision. The next production revolution requires quick and proactive policy making, as well as better orchestration across different policy domains. Foresight can assist policy makers by providing foundations for robust policies, reframing policy issues, and translating long-term concerns into aligned policy priorities. Furthermore, policy implementation is likely to be faster and more effective when key stakeholders are involved early on in shaping the policies. Foresight benefits, however, are far from being automatic: the chapter considers eight factors critical to achieving the benefits. Ultimately, beyond just foresight recommendations, policy makers must be prepared to act.

Nanotechnology is a general-purpose technology (GPT), which enabled numerous product and process innovations, as well as productivity and sustainability enhancements in nearly all existing market sectors. Nanotechnology has the potential to enable further innovations and establish new market sectors in the near future. Continuing advancement of nanotechnology requires substantial investment in research and development (R&D) and commercialisation. Investment should be supported by inter- and intra-national collaborations, providing virtual research infrastructures, which allow the sharing of otherwise prohibitively expensive equipment and foster interdisciplinary research ecosystems that are inclusive of academia, governmental research and large and small companies, in order to fully harness nanotechnology’s innovation power in all existing and in potentially new industry sectors. Novel business and innovation-funding models should be developed, which account for the increasing multidisciplinarity and the advancing digitalisation of innovation. Regulatory hurdles to the commercialisation of nanotechnology should be removed.

The People’s Republic of China (hereafter “China”) is the largest contributor to global value-added in manufacturing. In recent years many Chinese companies have made great progress in creating and using new production technologies. For example, China is now the world’s largest user of industrial robots. These developments have been accompanied by a series of major policy initiatives and related public investments, an overarching aim of which is to advance the use of digital technologies in manufacturing. China’s goal of increasing the knowledge content of domestic production will expand the range of markets in which China competes. But upgrading manufacturing in China faces complex challenges. Technological capabilities remain highly uneven across the business sector. Challenges exist not only in increasing government investment in science and innovation, but also in commercialising research, improving infrastructures, making markets work more efficiently, and encouraging private sector innovation. Policy also needs to cope with a range of related developments, such as labour-market disruption, the growing importance of cyber security and the need for improved policy co-ordination.

Industrial biotechnology involves the production of goods from renewable biomass instead of finite fossil-based reserves. Much progress has occurred in recent years in the tools and achievements of industrial biotechnology. Industrial biotechnology demonstrates that environmental protection can accompany job creation and economic growth. There are, however, several barriers to its deployment over a wide range of products. Some of these barriers are technical and need further research and development. Others stem from the fact that bioproduction is in direct competition with the fossil oil, gas and petrochemicals industries, which are many decades old, have perfected supply chains, large-scale economies, and receive subsidies. Yet another barrier concerns uncertainty about the sustainability of biomass as a feedstock for future production. Many types of policy are needed to realise the potential of bio-based production, from public support for research, to development of sustainability measures for biomass, to product labelling schemes for consumers, to education and training initiatives for the workforce.

At the start of 2015 the OECD began work on a two-year project entitled Enabling the Next Production Revolution. The work set out to better understand the economic and policy implications of a set of technologies that are likely to significantly affect production over the medium term.

Institutions for technology diffusion facilitate the spread and use of new knowledge and methods that can assist companies in adopting new manufacturing technologies. Such institutions also help companies to achieve objectives ranging from improved production efficiency to product development, strategic planning, and training. This chapter examines publicly oriented technology diffusion institutions and their rationale, organisation, and services. Case studies of varied approaches are presented, including dedicated field services, technology-oriented business services, applied technology centres, information exchange, and demand-side incentives, and effective practices and operational insights are distilled. Key policy suggestions include the need for greater recognition that strong institutions for technology diffusion, in conjunction with complementary framework measures, are essential for widespread deployment of the next production revolution. Technology diffusion institutions should be encouraged to share and refine their practices, build collaborative partnerships, and address missions of sustainability and responsibility. Particular attention is required to assist small and medium-sized enterprises (SMEs) and to address governmental failures in technology diffusion.

This chapter examines the potential environmental sustainability implications of 3D printing (also called “additive manufacturing”) as it displaces other manufacturing technologies, and lists top priorities for policy interventions to improve environmental sustainability. It considers several of the most widely used 3D printing technologies as they are today and describes trends related to 3D printing’s ability to supplant other technologies in the near future as this method evolves. This analysis compares the environmental impact of today’s typical 3D printing with two classic manufacturing methods, citing life-cycle assessments, scoring greenhouse gas emissions and other air pollutants, material toxicity, resource depletion, and other factors. It also explores how 3D printing will expand into more industries. While this chapter mostly concerns plastic processes, other materials such as metal are also considered. While widespread 3D printing would not automatically be an environmental benefit as practised today, technologies already exist that, if brought from the industry’s fringes to its status quo, could dramatically shift manufacturing towards more sustainable production. Since the industry is at a crossroads, well-placed incentives today might establish beneficial technologies for decades to come, to make widespread 3D printing an important part of a more sustainable future.

Increasing the rate of discovery and development of new and improved materials is key to enhancing product development and facilitating mass customisation based on emerging technologies such as 3D printing. Acceleration of materials discovery and development has been enabled by advances along multiple fronts, including capabilities of scientific instrumentation, high performance computing combined with more predictive computational methods for material structure and properties, and data analytics. Historically it has taken 15 to 20 years from laboratory discovery of new materials to their deployment in products. Systematic methods for accelerated materials discovery and development are still in early stages in the new digital era. Prospects are bright for realising a materials innovation ecosystem necessary to integrate new materials with digital manufacturing technologies to achieve new product functionality. A range of initiatives, gaps, and key policy issues to be addressed are discussed in this chapter.

On an almost daily basis, we hear of technological breakthroughs ranging from artificial intelligence and 3D printing, to self-driving vehicles. We are entering a world of “digital manufacturing” and “the fourth industrial revolution”. It is a pleasure, therefore, to present The Next Production Revolution: Implications for Governments and Business, an in-depth OECD assessment of the medium-term economic and policy implications of new and emerging production technologies.

This chapter presents a review of emerging trends in manufacturing research and development (R&D) relevant to the next production revolution. It is based on analysis of national government policies, foresight exercises and research strategies in selected OECD countries and other major economies. The review highlights growing attention to the themes of convergence (of research disciplines, technologies and systems), scale-up (of emerging technologies), and national economic value capture (from manufacturing innovation). These policy themes have in turn resulted in manufacturing research programmes and institutions adopting a broader range of innovation functions (beyond basic research), creating closer linkages between innovation system actors, and providing new types of innovation infrastructure (tools, enabling technologies and facilities). Case studies of selected initiatives illustrate the varieties of approaches and contexts across countries. The chapter aims to help inform discussion and stimulate debate about the design and management of manufacturing research institutions and programmes for the next production revolution.

This chapter contextualises the overall report and distils the main findings and policy ideas set out in the chapters on digital technologies, industrial biotechnology, nanotechnology, 3D printing and new materials. Also summarised and commented on are the main messages from the chapters addressing the following cross-cutting themes: institutions for technology diffusion, public acceptance and emerging production technologies, using foresight processes, emerging manufacturing research and development (R&D) priorities and policies, advanced manufacturing institutes in the United States, and how the next production revolution is unfolding in the People’s Republic of China. This introductory chapter also describes a number of additional policy considerations and provides a wider substantive background to the study, in particular by examining the following: the relationship between productivity and the technologies of the next production revolution; work, automation and new production technologies; policies for science and R&D; challenges for education and training; selected labour market developments; geography-specific policies; emerging challenges for intellectual property systems; the need for long-term policy thinking; and possible implications for global value chains. This chapter also points to themes which require further assessment.

This chapter examines how new information and communication technology (ICT) applications – in particular big-data analytics, cloud computing and the Internet of Things (IoT) – enable novel production and organisational processes, and business models, mainly in industrial sectors. The chapter focuses on the productivity implications of new ICT applications in early adopting firms in a number of industries (including automotive and aerospace) but also in traditional sectors such as agriculture. An assessment is provided of policy settings needed to realise the potential productivity and other benefits of digital technologies in production, while mitigating a number of associated risks.

In the decade of the 2000s, US manufacturing employment fell by one-third, 64 000 factories closed, manufacturing capital investment and output suffered, and productivity growth dropped. The US had been systematically shifting production abroad, and studies suggested that the decline in its production capability was affecting its innovation capacity, which had long been viewed as the country’s core economic strength. This chapter reviews the origins of the policy response to this dilemma, which came to be called “advanced manufacturing”. The chapter traces the way the foundational concepts were developed in a series of reports; explores how a new innovation system response was developed to strengthen the production system; examines the key new policy mechanism, the manufacturing innovation institutes, which is a complex public-private collaborative model to develop new production technologies and processes, combined with workforce education; and, reviews how the new institutes are working, lessons learned as they have started up, and possible enhancements that could expand their policy reach. These new approaches – an advanced manufacturing programme – if implemented, could play a role in strengthening the US manufacturing sector. They could also play a role in moderating the serious social disruption created by the decline in manufacturing.

Public acceptance of technology is a key factor in how innovation impacts society, and its consideration should therefore figure in policy making around the next production revolution. There is a persistent but misguided view that resistance to technology mostly stems from public ignorance about the true benefits of particular technologies or of innovation in general. Social science research shows that more important reasons for such resistance might be basic value conflicts, distributive concerns, and failures of trust in governing institutions such as regulatory authorities and technical advice bodies. In general, countries and innovators should take into account, to the greatest extent possible, social goals and concerns from the beginning of the development process. While it remains a challenge to realise this goal, best practices have emerged that can serve as a guide. These include funding social science and humanities in an integrated fashion with natural and physical science, using participatory forms of foresight and technology assessment to chart out desirable futures, and engaging stakeholders in communicative processes with clear linkages into policy. All of the above will help build trust and trustworthiness into innovation systems.

The next production revolution will occur because of a confluence of technologies. These range from a variety of digital technologies (e.g. 3D printing, the Internet of Things, advanced robotics) and new materials (e.g. bio- or nano-based) to new processes (e.g. data-driven production, artificial intelligence, synthetic biology). This report examines the economic and policy ramifications of a set of technologies likely to be important for production over the near term (to around 2030). As these technologies transform production, they will have far-reaching consequences for productivity, employment, skills, income distribution, trade, well-being and the environment.