The impact of I4.0 on work in the automotive sector in Romania and Spain

Type de publication:

Conference Paper


Gerpisa colloquium, Brussels (2023)


automotive, Case studies, Dacia, Ford, fragmented implementation, I4.0, Romania, Spain, Tier 1, tier 2


Background and research questions
In this paper we approach the rational of a fragmented implementation of I4.0 in the automotive sector in the transition to electric vehicles. We explore this issue elaborating on four case studies, two OEMs in Romania and an automotive tier-1 and a tier-2 in Spain.
The visit to the plants and first-hand interviews represent the paramount phase of our field study. Topics of the interviews encompass two main areas: (a) identification of automation technologies in the establishment, their process of adoption (drivers, obstacles, etc.), implementation and related changes (business model, supply chain, complementarities with other technologies); (b) impact of automation technologies on work, gender aspects and industrial relations. The set of interviewees covers different roles within the organization: at least one top manager (CEO, HR, production manager), technology specialists, trade unions. No line operators were interviewed.
The case studies offer different perspectives on the automotive sectors in two European semi-peripheries. In Romania, we interviewed two OEMs: i) Dacia in Mioveni (Renault-Nissan- Mitsubishi company) that produces vehicles, engines and transmissions, with 6000 employees; ii) Ford in Craiova (Frod Otosan Group) that produces vehicles and engines, with 3600 employees. In Spain, we interviewed two automotive suppliers in Zaragoza: Copo and Linde & Wiemann (L+W). Copo, with 220 employees, produces car seat padding for an Opel's tier-1 supplier located near the Opel plant in Zaragoza. L+W, with its 150 employees, is specialized in bending and stamping and realizes welding of subassemblies of car's structural parts and body. Both companies belong to multinational firms and play a dynamic role in the overall reconfiguration of their parent company in the automotive value chain.
The automation technologies considered in the field work encompass a broad range of artifacts, such as industrial robots, cobots, Automated/Automatic Guided Vehicle henceforth AGV, 3D printing, optical scanning, industrial software (such as Manufacturing Execution Systems, MES, Enterprise Resource Planning, ERP). Various degrees of integration of their operation are at stage in the information and communication systems (machine-machine, people-machine and people-people) across departments, within the establishments, and with suppliers and customers.
Main results
In the paper we analyse, first, the reasons behind the adoption of automation technologies that, despite some specificities, result to be similar for the four plants. Then, we compare the specific conditions undertaken to increase the efficiency of the production process, characterised by variability of product (car types and models), production costs reduction and zero errors targets. The need to reorganise the entire process, within and across plants, shows that lean production and digitalisation of information flows is far from being homogeneous within plants (across the various departments) and in the various suppliers of parts and components. In the four establishments, transition to electric vehicles production is under way, integrating new production lines and reorganising the current and products according the parent companies decisions.
Compared to the manual recording and analysis of production data, with MES, data are obtained in real time, however, to become effective, collected data must be interpreted and consequent actions must be undertaken. The implementation of MES implies a change in the mindset and culture inside the company at all levels (Colombari et al., 2023), but decision processes differ across the various plants. Organizational culture matters, and tasks and responsibility of middle management can vary a lot, as in the case of team leaders. While in OEMs we found departments where team leaders were just assigned supervision tasks over workers’ performance; in a tier-1 we observed team and shift leaders trained not so much with software progamming competences as in interpreting data and taking decisions on production on a daily/shift base.
In general, the automation process seems to be closely linked to the digitisation of information and communication flows, that are nevertheless managed differently in the four companies. Potentially, automation enables the collection of data which could be used to manage failure and wear prediction of devices and machineries. MES and advanced models of data analysis could be deployed to define more effective designs of maintenance and ensure most efficient production flows. However, at the current stage, big data are very far from being the new resource for growth: most of the collected (big) data are not analysed at all.
The overall increasing automation and digitalisation requires an increasing number of maintenance workers (whose recruitment relies also on upskilling of line operators) that are involved in the installation of automated processes and in controlling their working functionality. Evidence from our interviews highlight that providers of capital equipment make very limited use of data analytics over the installed equipment, suggesting another layer of fragmentation in the “holistic” paradigm.
The impact of automation on work is complex and not uniform (Krzywdzinski, 2017; Cirillo et al., 2021). On the one hand, it increased work efficiency and improved ergonomics for individual tasks, reducing the risks of heavy operations (i.e., loading large sheet metal parts for stamping), as well as of dangerous (i.e., welding), harmful (i.e., painting) or repetitive ones (as in the case of certain assembly operations). On the other hand, it increased mental stress in some phases of the labour process and challenged occupational perspective of fringe workers, becoming "in transition" workers, waiting for full automation displacing their tasks without an alternative one in which to be employed, or being "temporary", to support the waves of extra almost daily/weekly variability of demand.
In the four establishments, transition to electric vehicles production is under way, integrating new production lines and reorganising the current and products according the parent companies decisions.

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