Digital tools for pre-production planning

SHB doctoral candidates develop standard methods for Digital Factory

Task parallelism and frontloading in pre-production planning, lean serial production applying the zero-defects principle – a driving force in modern technology companies. The world of business is changing – a challenge to production planning, as well. However, given the large number of variants and very short development and planning cycles, it is difficult to achieve key objectives on schedule. These objectives include: ensuring that assembly lines are productive from the moment production is ramped up; keeping product manufacturing costs down; attaining a high level of product quality early in the product life cycle. “Digital Factory” makes it possible to meet the rising number of demands that will be placed on production planning in the future. As part of a joint project with Daimler, Steinbeis University Berlin’s transfer institute for Production & Engineering has developed a method for designing efficient planning processes using digital planning tools. The partners also created an implementation method that ensures successful use of Digital Factory in the long term.

Tobias Riegmann and Mathias Engel, doctoral candidates at the Steinbeis Transfer Institute, asked themselves two questions. One: how can “Digital Factory” be used in production planning and facilitate standardized, efficient planning processes? Two: how can we subsequently ensure long-term use of Digital Factory?

Once at Daimler, the experts designed a planning process built on three underlying principles. Used in combination with Digital Factory tools, these three principles – the model, the method and the system – became the basis of a standardized, universal planning method, also known as DiFOR (Digital Factory Operating Reference).

The reference model DiFOR is based on is a process map showing the workflows and structures of core production planning processes. Users throughout the company can take advantage of digital tools to carry out these processes. Thanks to a companywide standardized database, cooperating planning departments can now be synchronized, resulting in a variety of other synergy effects.

This is supported by an integrated planning method that makes it possible to match the DiFOR process map to company requirements, based on a criteria list. This method thus provides a “roadmap” for working with the reference model and tailoring it to company needs.

The DiFOR process map, adapted and instantiated for the specific project, is provided by the system via a web-based front-end application, based on Microsoft Sharepoint. The personal login to this in-house Web 2.0 application controls the view and the provision of required, project-related data. The process screen can be scaled individually to adjust granularity. Process training documents, which are based on modules, can be matched to needs. Feedback and inquiries can be managed by subject. Overall, this boosts the benefits of partnership between users, in both directions.

To define DiFOR parameters and pinpoint barriers to Digital Factory implementation, the team interviewed experts. These experts were end-users at European automotive companies, system suppliers, and consulting firms. The interviews with experts revealed that certain barriers crop up when Digital Factory is implemented in distributed inhouse production planning departments. These barriers were first categorized by four basic areas of influence (each a different “view”): the people, the organization, the processes, and the technology. Within each view, the barriers were then clustered into design areas. Finally, with various elements now bundled (four views, 51 barriers, 13 design areas, and 33 tools), the interrelationships were mapped on an “operational network of Digital Factory implementation”.
In total, 33 tools were developed, each based on individual design areas. These help overcome barriers to implementing Digital Factory in a distributed production planning network.

The team decided that the implementation strategy must be flexible enough to evolve at each stage, progressing step by step, based on the process applied. This sometimes involved users early on, also allowing for continuous improvement and learning during implementation. The 33 tools can be used flexibly at each stage.

In designing the implementation process, this “evolutionary approach” was maintained. The result was a four-phase procedure. The first phase involves setting up pilot projects to ensure high availability of Digital Factory methods and show benefits quickly. During this phase, the digital planning process map is essential as it not only makes it possible to identify the planning activities that can be supported digitally, it also enables a largely standardized planning process. After software has been selected, the consolidation phase begins. The objective of this intrinsically iterative phase is to establish specific best-practice approaches as standard Digital Factory methods throughout the entire production planning network. Here, the planning map is a shared element that serves to safeguard continuity between individual planning disciplines and the planning activities. The next phase, horizontal integration, networks all planning departments and plants that are planning the same product or stage of value-added (and thus have similar IT infrastructures). The final phase, vertical integration, ensures that even if a plant has only recently been incorporated, or it is working on higher levels of value-added, it can still be integrated into planning using digital tools.

The two methods developed by the team, DiFOR and iDIFA, address the key Digital Factory issues regarding implementation and subsequent use in industry. The methods have already proven suitable for practice in the planning departments of Daimler’s major assembly plants.


Prof. Dr.-Ing. Ulrich Günther | Dr.-Ing. Stephan Buerkner |
Dipl.-Wirt.-Ing. (FH) Tobias Riegmann | Dipl.-Wirt.-Ing. (FH) Mathias Engel

Steinbeis Transfer Institute, Production and Engineering Steinbeis University Berlin

Daimler AG (Mannheim)

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