Research

Construction Prozess Management

Real-time Control

Roman Oldenburg
Picture: Roman Oldenburg

Integrated Construction Control Center for Real-time Control of Construction Processes

Roman Oldenburg M. Sc.

Development Process of the Integrated Construction Control Center for Real-time Control of Construction Processes
Development Process of the Integrated Construction Control Center for Real-time Control of Construction Processes

The aim of the research is to develop a digital construction control center. This will allow for transparent statements about the current state and future development of complex construction projects at any time. The need for management measures can be assessed almost in real-time. To achieve this, system dynamic models will be developed together with project managers on selected complex, large scale construction projects. These models will be developed in workshops based on the knowledge and experience of the involved individuals. Knowledge gained through personal observation can complement the model development, as well as available “hard” and “soft” metrics. The models will be calibrated and validated using historical data. The information progressively stored in conventional management tools will be linked with the model to represent the current state of the overall system in near-real-time.

Currently, a variety of different tools is used to manage complex construction projects. Each is tailored to the specific needs of the respective disciplines and serves as a valuable repository of information. This information is periodically compiled and evaluated in a project report. The evaluation of information corresponds to a transformation of disposable knowledge into orientational knowledge and follows the mental models of the project managers. A mental model is the implicit understanding of how project success is achieved. Mental models can be incorrect and incomplete. They are particularly difficult for others to comprehend. Intuition is difficult to articulate. Between two reporting dates, management is in “instrument flight”. Individual metrics can be read, but a clear view of the big picture remains obscured.

System dynamic models can process quantitative information of all formats (management tools) as well as qualitative and descriptive information (mental models). The number of features that can be modeled and the feedback relationships between them is unlimited. Their dynamic behavior over time can be very well simulated using computer support. Based on the current state of the system, forecasts can be continuously made about its future development. The evaluation of information will henceforth be partially automated using the developed project models. In addition, the effects of interventions can be simulated in various scenarios, allowing to derive actionable recommendations.

Value stream oriented production planning

Paul Herrmann
Picture: Paul Herrmann

Integration of the value stream oriented production planning procedure into the work preparation of underground construction engineering

Paul Herrmann M. Sc.

Prudent, efficient and effective construction planning in the sense of work preparation is necessary for successful execution of construction projects. Such intensive work preparation also facilitates the integration of changed and unforeseen working conditions and challenges, which regularly arise during the construction process and require the continuous updating and adjustment of construction management planning. Task-oriented and collaborative methods for work design, as well as the planning and control of the construction process and the resources to be used (resource planning), are tools that systematically define processes and thus proactively create structures that, despite changing working conditions, contribute to improving productivity.

In contrast to work preparation for construction projects, comprehensive production planning is established in the stationary industry. One tool applied in this context is the so-called Value Stream Method. This method systematically analyzes production processes and the controlling information flows and implements improvements based on this analysis.

In construction projects, the Value Stream Method is rarely applied. The research aims to explore the causes of its cautious use and to develop proposals for the successful adaptation of this method to construction projects. Field trials will be conducted on selected subjects in the field of specialized civil engineering to analyze the target dimensions and areas of impact, test data collection and processing, improve visualization and representation with intrinsic and extrinsic references to the depicted processes, and systematically develop the method in the context of work preparation/construction execution. These empirically inductive field trials, which build on theoretically deductive considerations, form the basis for a process model for the efficient and effective application of the Value Stream Method in construction projects in specialized civil engineering as an element of Lean Construction.

Risk Management

Stefan Brach
Picture: Stefan Brach

Impact of the covid 19 pandemic on construction projects

Dipl.-Ing. Stefan Brach

As part of the research work, the impact of the covid 19 pandemic is being recorded and analyzed. For this purpose, working conditions on construction sites as well as claims and notifications are documented and evaluated. On this basis, recommendations for action will be formulated on how to deal with crises and the issue of business continuation risk in the construction industry in the future.

Multi-project Management

Baustelle
Picture: Jörg Fenner

Data-based multi-project management and effective control through data analytics

Saskia Erler M. Sc.

Development of a data-driven multi-project management system
Development of a data-driven multi-project management system

In the research work construction project data from the initiation, planning and execution to the handover of the object are recorded and systematically analyzed. On this basis, a concept of multi-project management is to be developed in the perspective of an industrial building owner, which enables a data-based and thus objective as well as comparable recording of the project status. Within this framework, the research work deals with the availability, structuring and processing of data in digital systems. Based on this, statistical methods and machine learning approaches are used to investigate re-occurring dynamics and data patterns in construction projects, which lead to the implementation of an early warning system, that can be used for effective control by the owner in multi-project management.