스마트공장 도입의 효과와 정책적 함의 (Smart Factory: Economic Impacts and Policy Implications)

Korean Abstract: 제조업과 IT의 융합으로 나타난 제조업 혁신기술의 발전은 기업에 새로운 기회를 제공하는 동시에 변화에 대응하지 못한 기업의 생존을 위협하고 있다. 주요국들은 소위 4차 산업혁명으로 불리는 산업의 디지털화에 대응하여 제조업 경쟁력을 강화하려는 전략을 내세우고 있다. 우리나라 정부는 ‘2022년까지 스마트공장 3만개 구축’을 목표로 중소기업에 대한 직접 지원을 통해 제조강국을 실현하겠다는 전략을 추진 중이다. 본 연구는 해당 전략으로 지원받은 사업체를 포함하여 우리나라 제조업체의 스마트 수준이 어느 정도인지, 제조업체가 더 스마트해지고 있는지 등의 근본적인 물음에서 시작한다. 사업체의 스마트 수준의 변화가 사업체의 성과에 어떠한 영향을 미치는지에 대한 분석도 되어 있지 않은 현실에서 본 연구는 계량경제학의 방법론을 적용하여 이에 대한 분석 결과를 제시한다(제2장). 연구자와 정책당국자뿐만 아니라 노동자들도 스마트화의 진전이 노동과 고용에 미칠 영향에 대한 관심이 높다. 본 연구는 스마트화를 데이터를 활용한 생산시스템의 변화로 인식하고, 노동을 대체하는 자동화와 차별하여 스마트화가 노동과 고용에 미치는 영향에 대해 분석한다(제3장). 더 나아가 사업체의 스마트화에 영향을 미치는 요인에 대해 분석하여 특정 기술의 도입만이 아닌 다른 중요한 스마트화 요인에 대해 분석한다(제4장). 스마트공장은 생산시스템과 관련한 소프트웨어 혹은 하드웨어의 설치만으로 완성되지 않는다. 디지털 기반 생산시스템의 운영능력과 운영과정에서 추출되는 데이터 분석능력을 갖추지 못한 공장에 대한 스마트화 지원은 오히려 비효율성을 가중시키는 결과를 초래할 수 있다. 본 연구의 결과는 공장의 스마트화는 기술적 변화뿐만 아니라 경영과 작업 방식의 변화가 함께 수반되어야 한다는 점을 정책에 반영할 필요를 역설한다. 본 연구에서는 중소⋅중견기업의 스마트화를 효과적으로 지원하는 방안을 구체적으로 제안하며(제4장), 우리나라 스마트 제조혁신 전략이 개별 공장의 스마트공장 도입을 넘어 실제 제조업의 경쟁력 강화로 이어지기 위한 새로운 제조업 혁신 거버넌스를 제시한다(제5장). English Abstract: As digital capabilities become more critical in firm survival and industry competitiveness, major countries put forward strategies to promote and support firms' digitization. The Korean government has also pursued policies to encourage firms, small and medium-sized in particular, to adopt smart manufacturing. The goal is to have 30,000 smart factories by 2022. Despite its importance and difference from traditional automation, there has been little effort to understand the economics of smart manufacturing. This report is the first comprehensive study to measure the level of smart manufacturing, examine its economic impacts, and identify the determinants of adopting the smart factory. Based on the concrete quantitative evidence, this study provides policy suggestions for the effective digital transformation of manufacturing. From a technical point of view, a smart factory is defined as "Digitization and networking of all processes, products, and resources." As the smart factory integrates the factory system to digitize and network all production activities―and thereby go beyond simple automation―it can improve the efficiency of the production process, flexibly cope with breakdowns and sudden changes in supply and demand, and even help to develop new products and predict future demands. We first measure the level of the smart factory by two factory-specific characteristics: (1) the degree in which all the production activities in the factory are interconnected systemically (system integration) and (2) the degree to which the factory collects, shares and utilizes data for decision-making (data share and use). To collect necessary information, we surveyed about 1,000 domestic plants in the Korean manufacturing industry. From the survey result, we find that the sample factories were generally low in the smart factory level, but there was a modest improvement between 2015 and 2017. We also find a significant gap between factories in both levels and change. Chapter 2 examines the effects of factory smartization on the three key performance indicators (KPI) of the factory: productivity, cost efficiency, and product variety. For productivity, we find that daily production increases when the smart factory level increases. We find similar effects on other KPIs, which are heterogeneous by the type of production process. For example, we find a significant reduction in the lead time only from continuous-process factories, while we observe a reduction in the defect rates, a cost-efficiency indicator, only from assembly line-process factories. For product variety, we find the most substantial positive effect from the batch (and job shop) process. Chapter 3 explores the employment effect of factory smartization and compares it to that of automation. While economists find negative impacts of individual technologies, such as robots and AIs, engineers argue that smartization, a system-wide change distinct from automation, creates new labor demand for constant reconfiguration and training of workers. This chapter tests the hypothesis by examining the relationship between planned smartization and predicted labor demand by worker groups (production workers, technical engineers, and office workers). The results support the engineers' prediction. While automation is expected to decrease the demand for all three classes, improvement in the production process is not likely to decrease the demand for technical engineers. Smartization in even greater scale - integration of all business activities - is expected to have no adverse effects on all three worker groups. Having said that automation and smartization are different in their job impact, this chapter also emphasizes that there is considerable heterogeneity across firms and workers. Production workers and office workers, young and old workers, and workers at low-level smart factories are those more vulnerable to production smartization. Policymakers should encourage firms to provide them with proper retraining and reallocation program. Given the effects of the factory smartization on performance and employment, it is important to understand what factors determine the level of smartization. Chapter 4 investigates the determinants including the adoption of technologies relevant to the smart factory with a focus on the role of complementary organizational features. We find that there is a complementarity between human resource management practices and technology adoption in driving smartization. Technology adoption leads to smartization, and such effect magnifies disproportionately with the level of structured human resources management. We also find other magnifiers, such as the presence of an ICT division and CEO's willingness to upgrade the manufacturing system. The complementarity between technology and organizational practices suggests the need to reconsider the current policy direction. First, before providing support, there needs to be an accurate diagnosis of the target firm's organizational practices, needs, and expectations for the effects of the smartization. This “pre-consulting & post-support” approach will be more effective than merely helping firms to introduce specific technologies. Second, we propose to build a platform that provides one-stop services for SMEs. Third, we make suggestions to make the government's support system smart (government smartization) to increase the effectiveness of the support. Chapter 5 concludes this study by proposing a plan to reform the governance for manufacturing innovation. The key message is that the private sector should play a central role in both policy-making and implementation process for policies to be effective in this transforming digital era. We suggest to organize a council by benchmarking the Germany’s Industrie 4.0 platform. The council is a network of representatives from business, science, government ministries and trade unions. The council is expected to present the economy- wide digitization strategy. We also argue that cooperation between SMEs and large corporations is crucial in pursuing smart manufacturing in the Korean business environment. We discuss possible policy measures to facilitate their cooperation and make the environment more favorable to SMEs.