the application of artificial intelligence and self-optimizing ... âIoT REVOLUTION IN OIL AND GAS INDUSTRY,â in Internet of Things and Data Analytics Handbook ...
THE IMPACT OF PROCESS AUTOMATION ON MANUFACTURERS’ LONG-TERM KNOWLEDGE 1 C. ,
2 C. ,
2 V. ,
1 C.
Gernreich, C. Bartelheimer, Wolf, Prinz, 1) Ruhr-Universität Bochum // 2) Paderborn University
THEORETICAL BACKGROUND • The application of digitalization techniques and digital technologies trigger a fundamental transformation process (Priyadarshy 2016). • Inherent automation tendencies offer a great potential to increase the productivity and quality of processes (Thatcher and Oliver 2001). • However, automation in manufacturing often neglects the value of an employee’s knowledge and skills related to the underlying processes (Mayer et al. 2011). RESEARCH QUESTION: How does the automation of manufacturing processes affect the long-term knowledge base in an organizational context?
EMPLOYEES AS KNOWLEDGE CARRIERS Proposition 1: Manual, non-automated manufacturing provides easy access to a knowledge base. PRODUCTION SYSTEMS AS KNOWLEDGE CARRIERS Proposition 2: Through process automation by the manufacturer himself, unrestricted access to a knowledge base is provided, while the required long-term knowledge diminishes. LOCUS OF AUTOMATION Proposition 3: Through the outsourcing of process automation, the access to a knowledge base is restricted, and the required long-term knowledge diminishes.
PRELIMINARY RESULTS
RESEARCH DESIGN
MANUAL/NON-AUTOMATED MANUFACTURING (PROP. 1)
QUALITATIVE RESEARCH APPROACH
Interviewee F: “Our employees know the respective areas. Both CEOs have the entire knowledge, except for the software development process. We have three people in code production, one person in software development, and three persons in technology. The employees can stand in for each other except in software related topics”
Primary data: semi-structured interviews Secondary data: observations, workshops „Yes, excessive automation at Tesla was a mistake. To be precise, my mistake. Humans are underrated.”
THEORETICAL (CASE) SAMPLING (1) Manual/ non-automated manufacturing (2) Automated manufacturing processes (3) Outsourced automation of manufacturing processes.
- Elon Musk, CEO of Tesla
RESEARCH PROCESS (1) Content analysis for each case (2) Cross-case analysis Case Industry Employees A Robotics (MAPM) 300 B C D
Recycling Management consultancy Household appliances
500 250 10,000
E
Steel
2,000
F
Electronics
7
G
Electronics
16,500
Interviewee Project Manager Head of R&D and Quality Senior Manager Digitalization Production Process Manager Process Technology Engineer CEO Production Process Manager
Duration 18 min.
60 min. 30 min. 32 min. 15 min. 55 min.
Table 1. Sample Description
Figure 2. Effect on Technology Knowledge
AUTOMATED MANUFACTURING PROCESSES (PROP. 2)
53 min.
Figure 1. Effect on Process Knowledge
Interviewee B: “When it comes to the overall concept of the machinery [...] the MAPM of the components falls behind. [...] We know how to interconnect the components, how they work with each other, in which order the components have to be set up, and which particle size works [...] that is our know-how, which I claim to persist.”
Figure 3. Effect on Asset Knowledge
CONCLUSION
OUTSOURCED
• Knowledge loss is related to increased automation even stronger effect for outsourced automation • Ongoing automation creates communication barriers, leading to a lower frequency of knowledge exchange further decreases the knowledge base and the ability to innovate processes
Interviewee A: “An intensive informative exchange between the manufacturer and the MAPM is essential for successfully automating manufacturing processes.”
IMPLICATIONS (1) Examine transferability to automation in service industry (2) Extrapolate our insights about knowledge base development considering different levels of automation or the application of artificial intelligence and self-optimizing production systems (Mayoral et al. 2018) (3) Organizations must diversify outsourcing activities and establish competence in arranging machinery and testing in real-world environments (4) Effects of increased automation on spatial and timely distance could play an important role for knowledge exchange and thereby process innovation potential
Scenario Manual
AUTOMATION OF MANUFACTURING PROCESSES (PROP. 3)
Knowledge Location
Knowledge Carrier
Knowledge Access
Internal
Human
High
Knowledge Base (based on interview) Process High (B, E, F) to middle (A, C)
Automated
Internal
Material
High
High (B)
Outsourced Automation
External
Material
Low
Middle (A, D)
Asset
Technology
High (F)
High (F)
Middle to high (B) Middle (A) to low (C)
Low to middle (B) Middle (C)
Table 2. Research Results in Data Analysis Matrix
GET OUR CONTACT
GET OUR PAPER
MEET US @ ICIS
HEAR OUR SLAM
REFERENCES Mayoral, V., Kojcev, R., Etxezarreta, N., Hernández, A., and Zamalloa, I. 2018. “Towards Self-Adaptable Robots: From Programming to Training Machines,” ArXiv:1802.04082. Priyadarshy, S. 2016. “IoT REVOLUTION IN OIL AND GAS INDUSTRY,” in Internet of Things and Data Analytics Handbook, H. Geng (ed.), Hoboken, NJ, USA: John Wiley & Sons, Inc., pp. 513–520. Thatcher, M. E., and Oliver, J. R. 2001. “The Impact of Technology Investments on a Firm’s Production Efficiency, Product Quality, and Productivity,” Journal of Management IS (18:2), pp. 17–45.
1282
