German Automotive Manufacturer Research Articles

Managing Finances in Scaled Agile Transformations: Insights from A Case Study of a German Automotive Manufacturer

Managing Finances in Scaled Agile Transformations: Insights from A Case Study of a German Automotive Manufacturer

Internal antecedents for systematic business model innovation: insights from the German automotive manufacturers

Internal antecedents for systematic business model innovation: insights from the German automotive manufacturers

Internal antecedents for systematic business model innovation: insights from the German automotive manufacturers

Internal antecedents for systematic business model innovation: insights from the German automotive manufacturers

Employee perspectives on value realization from data within data-driven business models

Firms are innovating data-driven business models (DDBMs) to realize value from data. Yet, making DDBMs work is challenging, and DDBMs often fall short of expected value realization. One reason for this shortfall is that firms do not know how employees, who decisively influence a DDBM’s value realization, view this complex and multi-facetted topic. We think it is necessary to understand the employees’ perspectives, the dimensions that build these perspectives and the characteristics employees are particularly interested in regarding value realization from data. We address this research gap by applying the Q-methodology to examine the perspectives among 70 employees across twelve DDBMs at a German automotive manufacturer. This yields eight perspectives, e.g., data advocacy, data caution or data practical. By exploring these perspectives, we provide a first groundwork on how employees view and appraise value realization from data which adds to the strive for mastering value realization from data within DDBMs.

Estimating the potential reduction in future sickness absence from optimizing group-level psychosocial work characteristics: a prospective, multicenter cohort study in German industrial settings

BackgroundAbsence from work due to sickness impairs organizational productivity and performance. Even in organizations with perfect work conditions, some inevitable baseline sickness absence exists amongst working populations. The excess sickness absence observed above this baseline rate has become the focus of traditional health promotion efforts, addressing preventable physical illness, health behavior and mental health at the personal level. However, a health and safety approach following the TOP-rule would consider work-group psychosocial work characteristics as a potential risk factor amenable to organizational measures. To date, there is a scarcity of studies relating psychosocial work characteristics to possible reduction of excess sickness-absence rates.MethodsWe aimed to estimate the potentially avoidable excess fraction of absence attributable to work-group psychosocial characteristics. We considered work-group averaged perception of psychosocial work characteristics as a proxy to the methodologically elusive objective assessment of organizational characteristics. Participants were recruited from multiple sites of a German automotive manufacturer with individuals nested within work groups. We predicted 12-month follow-up work-group sickness absence rates using data from a baseline comprehensive health examination assessing work characteristics, health behavior, and biomedical risk factors. We considered the quartile of work-groups yielding favorable psychosocial work characteristics as a realistic existing benchmark. Using the population attributable fraction method we estimated the potentially amenable sickness absence from improving work-group psychosocial characteristics.ResultsData from 3992 eligible participants from 29 work groups were analyzed (39% participation rate, average age 41.4 years (SD = 10.3 years), 89.9% males and 49% manual workers.). Work-group absence rates at follow up varied from 2.1 to 8.9% (mean 5.1%, 11.7 missed days). A prediction model of seven psychosocial work characteristics at the work group level explained 70% of the variance of future absence rates. The estimated reduction from improving psychosocial work characteristics to the benchmark level amounted to 32% of all sickness absence, compared to a 31% reduction from eliminating health behavioral and medical risk factors to the benchmark target.ConclusionsPsychosocial characteristics at the work-group level account for a relevant proportion of all sickness absence. Health promotion interventions should therefore address psychosocial characteristics at the work group level.

Prognostic Model Development with Missing Labels

Condition-based maintenance (CBM) has emerged as a proactive strategy for determining the best time for maintenance activities. In this paper, a case of a milling process with imperfect maintenance at a German automotive manufacturer is considered. Its major challenge is that only data with missing labels are available, which does not provide a sufficient basis for classical prognostic maintenance models. To overcome this shortcoming, a data science study is carried out that combines several analytical methods, especially from the field of machine learning (ML). These include time-domain and time–frequency domain techniques for feature extraction, agglomerative hierarchical clustering and time series clustering for unsupervised pattern detection, as well as a recurrent neural network for prognostic model training. With the approach developed, it is possible to replace decisions that were made based on subjective criteria with data-driven decisions to increase the tool life of the milling machines. The solution can be employed beyond the presented case to similar maintenance scenarios as the basis for decision support and prognostic model development. Moreover, it helps to further close the gap between ML research and the practical implementation of CBM.

Enabling value stream mapping for internal logistics using multidimensional process mining

Pen and paper-based value stream mapping (VSM) is the established tool for recording processes, identifying waste and deriving recommendations for action. However, today, its application in manufacturing industry requires a high level of effort and is challenging due to product and process complexity, as well as dynamics. To overcome these shortcomings, we are developing a methodology to apply process mining (PM) to internal logistics for a mixed-model assembly line. The methodology combines multidimensional process mining (MDPM) techniques with proven principles of lean production and VSM. Firstly, internal logistics is modelled using existing event data by automatically mapping physical logistics activities (e.g. transport, store). Secondly, to enable PM, the event data is transformed into enriched event logs. Thirdly, the MDPM approach contains (1) a discovery analysis, (2) a performance analysis and (3) a conformance analysis including a reference process classification for each individual part and process. Finally, a waste analysis and strategy for practitioners is designed to identify and prioritise wasteful parts and processes. The methodology has been applied and evaluated in a case study at a German automotive manufacturer. In the case study, we analysed 7500 parts and 15 reference processes. An analysis for each individual part and process has not been available yet. We could both identify part-specific root causes (e.g. a long lead time) and process-specific root causes (e.g. a low trace fitness). The main contribution of this paper is to provide an MDPM methodology for practitioners to enable a continuous recording, evaluation and waste analysis of each individual part and process within internal logistics.

Staff scheduling in job rotation environments considering ergonomic aspects and preservation of qualifications

Demographic change is a well-known influencing factor challenging social security systems in industrialized countries. In a manufacturing context, companies need to cope with an increasingly heterogeneous workforce in terms of qualification and impairments, as well as an increasing average age. The development of more standardized processes and the trend to move towards shorter lead times, paired with demographic changes in the workforce, reveal a strong importance of staff planning.A short-term staff planning system which generates job rotation schedules taking into consideration workers’ qualifications, the workplace’s ergonomic exposure, and the most recent allocations of each worker is sought to ensure the right worker is allocated to the right work place at the right time. The arising complexity of such scheduling problems is met in this paper by using a linear programming based heuristic, which solves the scheduling problem gradually for each rotation round and generates a holistic job rotation schedule for an entire workday.The presented approach to short-term staff scheduling is implemented in a VBA-based software prototype and was tested in the final assembly line of a German automotive manufacturer.

Autonomous Driving — a Challenge for the Automotive Industry

The automotive industry is one of the most important industries in Europe. This industry is responsible for 14% of total production and capital investment in the European manufacturing sector, and in Germany the share amounts to 22%. Structural change within this crucial sector is of relevance for the whole economy. Along with alternative propulsion systems such as electromobility, (semi-)autonomous vehicles are one of the big trends in the automotive industry. For established providers, the possibility of disruptive change poses a threat to existing markets, while a gradual introduction of new technologies also increases competition. Nevertheless, with their strong market position in the premium segment and especially their relevant research activities, European and especially German automotive manufacturers are well placed to successfully master the coming challenges in the automotive market.

Model Based Requirements Engineering for the Development of Modular Kits

The introduction of modular design increases complexity within product development and especially within Requirements Engineering. To handle this complexity, the approach of Model Based Systems Engineering is applied in this contribution. First, the origins of complexity in modular product development are introduced. Key challenges within Requirements Engineering are drawn up and then verified. A modeling method for requirements of modular kits is introduced and validated in the series development of hybrid drivetrain systems at a German automotive manufacturer. Increases in quality and a requirements reusability of over 80% were achieved. Thus, the capability of the modeling method is verified.

Efficient Use of Sounding Board Method at Project Milestones and its Potentials for Virtualization

Project milestones in major product development projects are often the only possibility to discuss critical points with all relevant stakeholders. This is even truer in the context of globalization as these projects are run by worldwide spread teams integrating a growing number of stakeholders. One way to improve the involvement of all stakeholders is the application of the Sounding Board Method which concentrates on the content of feedback while suspending defending of results or ideas. In this paper the authors present a case study which was conducted with a German automotive manufacturer showing how to adapt the Sounding Board Methods for the efficient use at project milestones. In this context it is shown how collective intelligence can be used also for non-virtual collaboration. Subsequently the authors present a study outlining possibilities to implement the Sounding Board Method also for virtual project milestones in the future.

Modeling of Manufacturing Technologies During Ramp-up

The production ramp-up is of increasing importance for the manufacturing industry and has a significant impact on the product's success in terms of costs and time to reach full capacity utilization (time-to-volume). During the production ramp-up the instability of the production system and the quality of manufactured products are significantly influenced by the manufacturing technologies deployed. Furthermore, an analysis of the existing approaches to optimize production ramp-ups has shown that the selection and optimization of manufacturing technologies regarding the ramp-up targets is still insufficiently considered. Therefore, the aim of this paper is the development of a new ramp-up model that enables a prediction of the ramp-up behavior of manufacturing technologies and a selection of the most suitable one according to the given ramp-up situation. Firstly, different approaches from the field of ramp-up optimization and manufacturing technology evaluation are discussed, and the deficits are pointed out. Secondly, dynamic impact factors on the ramp-up performance of manufacturing technologies are systematically identified. Thirdly, the impact factors are transferred into a new analytical model which also considers stochastic influences on the ramp-up behavior. Fourthly, the analytical model is implemented into a hybrid simulation model, which is based on a combined discrete event and continuous flow simulation. The resulting simulation model can be utilized for the calculation of ramp-up curves for different manufacturing technologies as well as for the evaluation of the ramp-up performance of the technologies investigated. Finally, the model is validated with a use case from a German automotive manufacturer.

Institutional and cultural barriers to transferring Lean production to China: Evidence from a German automotive components manufacturer

Our qualitative study of a globally operating German automotive components manufacturer demonstrates how certain cognitive dispositions and behaviours of Chinese employees acted as barriers to the transfer of the firm’s Lean production system to its subsidiaries in China. We analyse how these barriers were rooted in the Chinese institutional and cultural context, thereby contributing a new micro-level perspective to business systems literature. Our findings further suggest that manufacturing in China will not be truly ‘Lean’ in the near future, which may place constraints on China’s technological development at a larger scale.

Integrated and Modular Design of an Optimized Process Architecture

Global economic integration increased the complexity of business activities, so organizations are forced to become more efficient each day. Process organization is a very useful way of aligning organizational systems towards business processes. However, an organization must do more than just focus its attention and efforts on processes. The layout design has also a significant impact on the system performance.. We contribute to this field by developing a tailored process-oriented organizational structure and new layout design for the quality assurance of a leading German automotive manufacturer. The target concept we developed was evaluated by process owners and an IT-based process simulation. Our results provide solid empirical back-up in which the performance and effects are assessed from a qualitative and quantitative perspective

Reflecting communication: a key factor for successful collaboration between embodiment design and simulation

The need for integration of computer-aided design and computer-aided engineering environments stems from the business priority to reduce product cycle times. It is exacerbated by the coexistence of two different paradigms: a topological one in embodiment design and a functional one in simulation. This dualism places increasing demands on human communication between design and simulation engineers. This paper claims that reflecting communication is a key factor for successful collaboration. Reflection is used in both senses of the Latin word ‘reflectare’: to trigger active thinking about and consideration of communication, as well as to mirror perceptions of a given situation by people collaborating. The paper reports on the development and application of a maturity-grid approach to diagnose the current and desired states of communication between design engineers and simulation engineers in the car body development of a German automotive manufacturer. Results include three themes: one, the importance of understanding of the collaborators’ information needs; two, the importance of orientation, e.g., indicated by the engineers’ overview of sequence of tasks in the design process; and three, the importance of reflection.

Quality Management throughout the value-added chain

After intensive discussions between automotive manufacturers and suppliers in the VDA (German Association of the Automotive Industry) managing board, an agreement for the safeguarding of joint quality in the German automotive industry was developed in 2005. Through a stronger process-orientation and synchronisation of the supply chain, the German automotive manufacturers and suppliers were able to recapture their quality leadership.

Auto producer opts for in-line plant

GERMAN automotive component manufacturer Menzolit-Fibron has installed a Dieffenbacher direct process press line for the production of composite underbody panels for the Volkswagen Group. This is a short news story only. Visit www.reinforcedplastics.com for the latest plastics industry news.

Exchanging Preliminary Information in Concurrent Engineering: Alternative Coordination Strategies

Successful application of concurrent development processes (concurrent engineering) requires tight coordination. To speed development, tasks often proceed in parallel by relying on preliminary information from other tasks, information that has not yet been finalized. This frequently causes substantial rework using as much as 50% of total engineering capacity. Previous studies have either described coordination as a complex social process, or have focused on the frequency, but not the content, of information exchanges. Through extensive fieldwork in a high-end German automotive manufacturer, we develop a framework of preliminary information that distinguishes information precision and information stability. Information precision refers to the accuracy of the information exchanged. Information stability defines the likelihood of changing a piece of information later in the process. This definition of preliminary information allows us to develop a time-dependent model for managing interdependent tasks, producing two alternative strategies: iterative and set-based coordination. We discuss the trade-offs in choosing a coordination strategy and how they change over time. This allows an organization to match its problem-solving strategy with the interdependence it faces. Set-based coordination requires an absence of ambiguity, and should be emphasized if either starvation costs or the cost of pursuing multiple design alternatives in parallel are low. Iterative coordination should be emphasized if the downstream task faces ambiguity, or if starvation costs are high and iteration (rework) costs are low.