Cobots in SMEs: Implementation Processes, Challenges, and Success Factors
Purpose: This study delves into understanding the processes, challenges, and determinants of success concerning the implementation of collaborative robots (cobots) in small and medium-sized enterprises (SMEs). With a keen focus on European manufacturing SMEs, the research seeks to highlight the barriers these entities encounter when integrating cobots and offer solutions grounded in empirical evidence.
Methodology: A qualitative exploratory case study methodology was employed for this research, embracing an inductive approach that lets theory emerge from the data itself. The study closely analyzed five manufacturing SMEs across varied industries and of different sizes, such as metal and machining, glass manufacturing, and more. These chosen SMEs have successfully integrated at least one cobot into their operations, making them ideal subjects to gain comprehensive insights into cobot implementation across different organizational contexts.
Findings: The study identified three primary barriers hindering the smooth implementation of cobots: technical, organizational, and cultural. The technical realm encompassed issues like programming intricacy and safety assessment. Organizational challenges touched upon job redesign and a dearth of integration know-how, while the cultural barriers echoed fears of job loss, safety apprehensions, and prevailing skepticism. However, amidst these challenges, the study also pinpointed crucial success factors. These include possessing a clear vision of cobot advantages, fostering open innovation, initiating pilot projects, maintaining transparent communication, and actively involving employees. Addressing the identified impediments while leveraging these success factors is pivotal for reaping the full benefits of cobot technology.
Practical implications: The study highlights the potential of cobot adoption for enhancing competitiveness in SMEs but also acknowledges the challenges they face. Its insights benefit SME managers by guiding effective cobot implementation strategies tailored to their unique situations. Policymakers can also use this research to design initiatives and policies that promote cobot adoption, fostering innovation and competitiveness in the manufacturing sector, benefiting SMEs and the industry as a whole.
(Best) Practices in the Integration of Social and Digital Decision - Making Approaches Across Industries
Purpose: The EINST4INE report aims to provide an in-depth analysis of how digital technologies integrate into human decision-making processes, presenting real-life applications and case studies. The report focuses on how digital tools are used to facilitate decision-making, particularly at the interface between digital and physical environments.
Contribution: The case study "Using Simulations to Improve Decision-Making Through Cobot Implementation" has been contributed to this report, aligning with the overall objectives of understanding and implementing digital technology integration in decision-making. This case study exemplifies the practical application of digital simulations to enhance decision-making in manufacturing.
Methodology: This case study, originally conducted by Raza et al. (2020), explores the use of computer simulations in optimizing the integration of collaborative robots (cobots) in a Danish SME's manufacturing process. The study utilized Tecnomatix Process Simulate software to create 3D animations and test various workcell layouts. Involving employees through a PDCA (Plan, Do, Check, Act) approach improved process understanding and acceptability.
Findings: The study identified significant benefits of using simulations in cobot implementation. Optimized workcell design included adding an underutilized CNC grinding machine, with the robotic arm switching tasks every 30 minutes. This approach improved the vertical grinder’s cycle time from 28 to 24 seconds and increased the CNC machine’s productivity from 8 to 24 hours a day. Simulations were shown to be effective in investigating technological and economic feasibility before actual implementation.
Practical implications: The study provides insights into overcoming underutilization issues in cobot integration. It highlights the importance of simulations and employee involvement in the decision-making process, demonstrating significant improvements in productivity and efficiency. Future research directions include exploring the economic feasibility of simulation software for SMEs, the impact of employee involvement in decision-making, and the role of augmented reality (AR) in enhancing decision-making and training.