Adoption Of Automation Technologies Research Articles

Impact of smart factory adoption on manufacturing performance and sustainability: an empirical analysis

PurposePrevious studies have focused on explaining the developmental paths and the relevant skills necessary for smart factories, based on an extensive review of the literature. Unfortunately, there is a deficit of empirical analyses that present an in-depth overview of smart factory development. Although the literature supports the benefits of smart factories, it remains unclear whether there should be government intervention (GI) to facilitate or regulate such adoption. This study will provide an in-depth empirical analysis of smart factory adoption (SFA) and its role in manufacturing performance (MP) and sustainable manufacturing (SM).Design/methodology/approachThis study used non-probability convenience and referral sampling techniques for data collection. This approach considered production managers from each company that participated in the survey questionnaire; thus, each production manager represented one firm. A total of 240 managers from several manufacturing companies participated in the study. This study employed direct and moderating hypotheses tested using PROCESS Macro, which Andrew Hayes developed for SPSS.FindingsThe study identified three fundamental elements of a smart factory: manufacturing big data (MBD), process automation (PA) and supply chain integration (SCI) and analyzed them individually to see how they affect MP. According to the results, building a smart factory has positive and significant impacts on MP and SM. Furthermore, this study explores the role of GI in promoting smart factory deployment for both production performance and sustainable production. The study found that GI did not have a significant moderating effect but did have a positive relationship with SM.Research limitations/implicationsThis study contributes to the literature on smart factories by examining the impact of SFA on MP and SM. This provides a more comprehensive overview of the potential benefits of smart factories across various aspects, such as the application of big data, adoption of automation technology and integration of the supply chain. This study suggests that managers and decision-makers consider investing in smart factory implementation to improve factory productivity and enhance sustainability. Policymakers and government officials can promote the adoption of smart factories by providing incentives, funding, and resources to manufacturing firms.Originality/valueThere is a scarcity of research measuring the actual performance of manufacturing firms that have already adopted smart factories, and this study seeks to address this gap in the literature. This study focuses on the implementation of manufacturing big data, process automation and supply chain integration and how the adoption of these technologies improves MP and provides a SM environment by conducting a real-time study of manufacturing organizations. This study presents an initial effort to explore the role of government involvement in promoting smart factories.

Equipment and Operations Automation in Mining: A Review

The mining industry is undergoing a transformative shift driven by the rapid advancement and adoption of automation technologies. This paper provides a comprehensive overview of the current state of automation in mining, examining the technological advancements, their applications, and the prospects of automation in this critical industry. A key focus of this paper is the impact of automation on the safety and efficiency of mining operations. Highlighting the successful implementation of Automated Haul Truck Systems (AHSs) in surface mining. Additionally, this paper explores the development of automation in underground mining and its challenges, particularly limitations in communication and localization, which hinder the development and deployment of fully autonomous systems. It also provides an exploration of the challenges associated with widespread automation adoption in mining, including high initial investment costs, concerns about job displacement, and the need for specialized skills and training. Looking toward future advancements in enabling technologies will be critical for furthering automation in mining. Machine learning and AI will play an increasingly critical role in intelligent automation, enabling autonomous systems to adapt to dynamic environments, optimize processes, and make informed decisions. This paper provides a look into human–robot collaboration in the future of mining. As the industry transitions toward greater automation, it is essential to consider the evolving roles of human workers to foster a collaborative work environment. This involves prioritizing human safety, providing adequate training, and addressing concerns about job displacement to ensure a smooth transition toward a more automated future.

Robotic and Autonomous Systems (RAS): Dynamic Modeling of Cyber-physical Environments

Dynamic modeling of nonlinear systems in cyber-physical contexts is necessary for understanding and predicting complex behavior. Enabling accurate representation of intricate interactions between cyber and physical components is crucial for enhancing control systems, predicting maintenance requirements, and enhancing resilience. This article presents industrial automation and robotics, taking into account the circumstances in developing economies. The importance of studying and using industrial automation and robotics can be attributed to the complexity of today's industrial setup and the pressing demand for increased production quantity and quality. Finding current initiatives and chances for more research was the aim of the examination. When it reaches innovation maturity, there is a dearth of study on the application and adoption of automation technologies and even less on technology innovation or prototyping. A more recent development has been an increase in the amount of research being done on industrial production technologies, especially additive manufacturing. Research on non-robotic cyber-physical systems, such as IoT connection, drone technologies, and actuator and actuator technologies specifically geared towards the construction industry, is minuscule. This research significantly advances dynamic modeling methodologies by creating a comprehensive and adaptable strategy tailored to the complexities of cyber-physical systems.

Why reshore? Evidence from Swedish firms

Reshoring, which refers to the relocation of previously offshored activities back to the home country, is a topic of growing interest in the literature. Two primary motivations for reshoring have been identified: the adoption of automation technology by firms and rising wages in offshoring destinations. In this study, we propose a novel method for identifying and quantifying reshoring using micro-data from Sweden. We then apply this measure to examine the validity of the two reshoring motives. Our findings indicate that reshoring is positively associated with technological advancements within firms, while we find no evidence to support the notion that rising income in offshoring countries prompts reshoring.

Automation technologies and the risk of substitution of women: Can gender equality in the institutional context reduce the risk?

This study investigates how the institutional context in terms of gender equality (in general and in the education and work components) affects the risk of substitution faced by European women, i.e., their risk of being replaced by automation technologies. To this aim, the risk of substitution is estimated by applying the task-based approach and by considering which skills cannot be automated (i.e., perception and manipulation, creative intelligence, and social intelligence). Then, the influence of the institutional context on the risk of substitution is evaluated. European women face a slightly lower risk of substitution than men (0.5755 versus 0.5816). In institutional contexts where gender equality is high, women and men face a higher risk of substitution, but the gender gap in this risk increases in favour of women, who face a significantly lower risk than men. Since automation reduces the general gap women face in society and gender equality in the institutional context contributes to reducing this gap, European policies should promote gender equality in the institutional context to foster a narrower gender gap following the adoption of automation technologies.

Global Value Chains and the Adoption of Automation Technology

This study investigates the relationship between the GVC integration of industries and their adoption of automation technology. I argue that integration into GVCs through forward and backward linkages of industries affects their adoption of automation technology positively through a learning and competition effect. Using a panel of industries from seven countries spanning 1993-2016, I provide evidence that backward linkages has a positive effect on the adoption of automation technology, while forward linkages is not significant. Furthermore, I investigate the importance of trade partners by taking into account the origin of intermediate imports and the destination of intermediate exports. Interacting forward linkages with intermediate exports to China shows that exporting more domestic value content in intermediate exports to China has a negative effect on the adoption of automation technology.

Examining the push factors for adoption of automation in a Malaysian manufacturing SME

The purpose of this paper is to examine the push factors for the adoption of automation technologies in a manufacturing small and medium enterprise (SME). A case study method is used to address the research questions with data collected from interviews with the key people in the organisation, a documentary review and observations of the company production processes. The Technology, Organisation and Environment (TOE) model in which the technological, organisational and environmental aspects define the process of technology adoption is used to analyse the data. The results show that the production process in the SME is semi-automatic and labour intensive. Although the staff lacks knowledge and expertise of technological trends, the top management is committed to change and innovation, and the staff's awareness of the cultural change that is required acted as a push factor for automation. The other factors that pushed the technological advancement in the production process was the need to optimise the production process for manufacturing flexibility, address the waste and quality issues faced by the company and meet customers' demands for customisation and quality products so as to ensure the sustainability of the company.

The Level of awareness of automation technology in the construction industry

The rapid development of infrastructure in a developing country like Nigeria may require the construction industry to totally embrace the innovative and advance technique of construction through the adoption of automation technology, so as to make construction project more valuable, enhance projects performance and stay competitive in the global and international industry. This study is strictly tailored towards investigating the level of awareness of the automation technique identified in the literature review section of this study. The study employed a cross-sectional survey design using a quantitative approach. A total of 191 construction professionals which include majorly the Architect, Builder, Engineer and Quantity Surveyor were the respondents for the study using a well-structured questionnaire. The questionnaire was designed on a five (5) point Likert-type scale having 5 sections of question in all. Data analysis were done using MIS, SD, Kruskal-Wallis and SNK Test. Twenty (25) automation techniques were pin-pointed from previous literature and materials that are linked with automation in construction industry. Study revealed that Computer Aided Design (CAD), cranes and Building Information Modelling (BIM) are the top three (3) techniques that are most aware of in the construction industry, while Concrete electric and infrared curing system, Humanoids and Contour crafting robots has the least rating. The study recommended seminars and workshop themes that are tailored towards the benefit of adopting automation in the construction industry. However, this research focused on level of awareness of automation techniques, future research can focus on cost implication of those techniques

A Research Roadmap for Off-Site Construction: Automation and Robotics

The development of a research roadmap was undertaken to further the activities of a joint industry-university-government initiative in off-site construction research in Canada. The roadmap identifies the general research areas of structural design, construction materials, building science, advanced manufacturing, logistics and transportation, automation and robotics, and digitized construction. The development of the roadmap included a broad literature review of peer reviewed academic journals, select conference proceedings, and industry publications. The review of recent research in these areas was analyzed from the perspectives of application area, technology area and innovation phase. The purpose of the analysis was to identify the current activities and opportunities for further research. For example, in the area of automation and robotics, the results showed the majority of construction automation research relates to the actual production phase, as opposed to planning or operations. In terms of innovation maturity, little research is being undertaken with respect to the implementation and adoption of automation technologies, and very little research in technology development or prototyping. In addition, applied research is being conducted at approximately half the rate of basic research. A more recent trend has been greater research interest in industrial production technologies, particularly in additive manufacturing. Very little research is being conducted with respect to non-robotic cyber-physical systems including, IoT connectivity, drone technologies, or construction focused actuator and manipulator technologies. This paper will discuss the broader results of the research roadmap with a focus on automation and robotics.

Does Technology Substitute for Nurses? Staffing Decisions in Nursing Homes

Over the past 10 years, many healthcare organizations have made significant investments in automating their clinical operations, mostly through the introduction of advanced information systems. Yet the impact of these investments on staffing is still not well understood. In this paper, we study the effect of information technology (IT)-enabled automation on staffing decisions in healthcare facilities. Using unique nursing home IT data from 2006 to 2012, we find that the licensed nurse staffing level decreases by 5.8% in high-end nursing homes but increases by 7.6% in low-end homes after the adoption of automation technology. Our research explains this by analyzing the interplay of two competing effects of automation: the substitution of technology for labor and the leveraging of complementarity between technology and labor. We also find that increased automation improves the ratings on clinical quality by 6.9% and decreases admissions of less profitable residents by 14.7% on average. These observations are consistent with the predictions of an analytical staffing model that incorporates technology adoption and vertical differentiation. Overall, these findings suggest that the impact of automation technology on staffing decisions depends crucially on a facility’s vertical position in the local marketplace. The online appendix is available at https://doi.org/10.1287/mnsc.2016.2695 . This paper was accepted by Chris Forman, information systems.

Immigration, Skill Mix, and the Choice of Technique

Using detailed plant-level data from the 1988 and 1993 Surveys of Manufacturing Technology, this paper examines the impact of skill mix in U.S. local labor markets on the use and adoption of automation technologies in manufacturing. The level of automation differs widely across U.S. metropolitan areas. In both 1988 and 1993, in markets with a higher relative availability of less skilled labor, comparable plants - even plants in the same narrow (4-digit SIC) industries - used systematically less automation. Moreover, between 1988 and 1993 plants in areas experiencing faster less-skilled relative labor supply growth adopted automation technology more slowly, both overall and relative to expectations, and even de-adoption was not uncommon. This relationship is stronger when examining an arguably exogenous component of local less-skilled labor supply derived from historical regional settlement patterns of immigrants from different parts of the world. These results have implications for two long-standing puzzles in economics. First, they potentially explain why research has repeatedly found that immigration has little impact on the wages of competing native-born workers at the local level. It might be that the technologies of local firms - rather than the wages that they offer - respond to changes in local skill mix associated with immigration. A modified two-sector model demonstrates this theoretical possibility. Second, the results raise doubts about the extent to which the spread of new technologies have raised demand for skills, one frequently forwarded hypothesis for the cause of rising wage inequality in the United States. Causality appears to at least partly run in the opposite direction, where skill supply drives the spread of skill-complementary technology.