International Conference on Engineering Design

Journal of Engineering Design, 2013

Research for improving the design process has become crucial in new work organisations. Today, projects involve more and more activities and work groups which must be efficiently coordinated. In this paper, a method for structuring cooperative activities in order to improve its global performance is proposed. This methodological approach is based on matrix modelling and graph theory to represent and to structure information dependencies and can be used to specify collaborative frameworks like Web technology environments. Knowledge of a specific design process depends on acquired experience in relatively similar projects. That is why we refer in this work to standards like ISO 9001 requirements and Capability Maturity Model Integration (CMMI). CMMI models are collections of best practices that help organisations to improve their processes. Classical methods decompose a project into several work groups which are then scheduled. This first decomposition level is supplemented with a more detailed structuring level in order to control the size of the working teams. The steps of the design process being defined and planned, the responsibilities inside the working groups are specified. Finally, the method proposes to identify the coupled pairs of actors who generate the best interface for the effectiveness of the cooperative work.

2005

This paper presents a case study about improvements of collaborative design tools in the automotive industry. The objective is to propose some specifications for the development of a particular information system. This system, integrated into the designers' CAD environment, shall support a method to integrate customer requirements into the design process. The problem of building up a project memory, in order to keep track of the requirements and their evolution (situated in their initial context) is also taken into consideration. The investigation shows the importance to find connections between different categories of agents, each of them having different rationales, objectives, representations, languages or tools. The results presented in this paper are the outcome of a field research carried out in a huge car manufacturer, in engineering design teams.

… Conference (DSM'07), …, 2007

INTRODUCTION For the design and development of complex technical products, communication between staff who work across functional and organizational boundaries plays an important role. However, the quality of communication is hard to measure. One method to assess communication is the Communication Grid Method (CGM) [1, 2]. The CGM is a maturity-based form of self-assessment to reflect on different factors influencing communication in product development. The factors belong to manifold areas influencing communication, such as the organizational structure, the company culture, teamwork, different aspects of information transfer and availability as well as several aspects of product representations. In a number of CGM-based studies, designers and managers from a number of industry sectors gave insight into their communication situation by scoring the current state of 24 factors influencing communication. To do so, the participants chose between four maturity levels, adapted from the learning types by Argyris & Schön [3], for each factor influencing communication. This data were used in the presented study to explore interrelations between the different factors describing communication. Within the correlations, a number of structural patterns were ascertained.

Design Studies, 2002

Design collaboration requires participation of individuals and coordination of design information and tasks. Team organization is one of the major tasks in design collaboration, because it can affect design communication and performance. This paper provides a basic understanding of the role of organization in design collaboration and how it affects design communication and collaboration by empirical case studies and design experiments. The results of case studies in architectural practice and design studios and a process model of design collaboration are presented. The study suggests that a structured organization can facilitate design communication and consequently contribute to the success of the design project. Computer supported collaborative work requires managing design tasks as well as information flows, and supporting three levels of communication, including individual, group and project. k

2013

Project information management research enables the efficient exchange of information, but does not effectively communicate process. Design process management research effectively communicates processes, but with methods too inefficient to be adopted in practice. The lack of methods for effective and efficient design process communication manifests as a struggle for Architecture, Engineering, and Construction industry professionals to: (1) collaborate within projects, (2) share processes between projects, and (3) understand processes across projects to strategically invest in improvement. These struggles motivate the paper's first contribution: a research method for evaluating a design management methodology's ability to effectively and efficiently communicate design processes. As a second contribution, this paper validates the Design Process Communication Methodology (DPCM). DPCM specifies elements and methods for exchanging and organizing digital information to support knowledge-intensive design processes. Cloud computing enables the operationalization of DPCM as a tool that enables interaction with a project's information. Results from this operationalization demonstrate that designers employing DPCM accurately capture processes with little effort. When collaborating, improved process clarity and information consistency result in less rework, and positive iteration enables increased consideration of multi-disciplinary design trends. Designers share processes between project teams with fewer process mistakes. DPCM enables the understanding of processes providing more insights into the relationships between design integration and project performance; and more opportunities for strategic investment in improved processes.

International Journal of Production Research, 1999

It is characteristic of engineering design that precedence relationships among the constituent design tasks contain information¯ow con¯icts. The existence of these con¯icts with the lack of formal methods to manage themrender the development cycle time unpredictable. This paper discusses a qualitative approach to engineering design management from an information structure perspective. The objective is to model, analyse and manage the interactions manifested by the information exchanges within the design process. We introduce the notion of Structural Sensitivity Analysis (SSA), which is devised based on two measures of information dependency among design tasks: Sensitivity and Variability. Those two measures of dependency enhance the classical design structure matrix method and allow for more complex analysis to be performed.

2004

The purpose of this research was to determine how team design and project management (planning and tracking) affected planning and design performance and the people involved in the process. A laboratory study was conducted to evaluate three factors: team design (individuals versus groups of three), project support (no project support versus manual project support versus automated project support), and the engineering design life-cycle, which includes conceptual design, preliminary design, and detailed design. There were six observations per treatment, involving a total of 72 undergraduate engineering students. The impact of these factors were evaluated for planning time, design cycle time, cost effectiveness, cost variance, schedule variance, mental workload, and job satisfaction. For treatments that called for groups, group process was evaluated in addition to group workload. The results showed groups took 61% more time to plan their projects compared to individuals (p<0.01). Planning time was 31% longer for participants with manual support compared to those with automated project support (p<0.01). Schedule variance (p<0.01) and cost variance (p<0.001) decreased 24% and 23%, respectively, over time during the design process. The design cycle time was 17% longer for participants without project support compared to those with automated project support (p<0.05). During design, groups and individuals allocated their time differently (p<0.05). Mental workload, measured with the NASA Task Load Index (TLX), showed workload increased 16% over time (p<0.001). In addition, the combination of design phase and project tracking support affected the TLX (p<0.01). Job satisfaction was 5% lower at the end of the design project compared to the beginning of design (p<0.05). From the analysis on group process, the type of project support affected the group process during planning. Groups with manual support interacted 83% more than those with automated support (effective behaviors: p<0.01; ineffective behaviors: p<0.05). During design, the roles individuals played within the group affected how much they contributed to the group's process (effective behaviors: p<0.0001; ineffective behaviors: p<0.01).

2002

Abstract: Before implementing a PDM-system within a company, the internal processes of product and process development and the information handled herein should be organized well. To enable this organization, one should be able to see the bottlenecks and therefore the working methods and the documents involved should be made transparent.

2004

The premise of this research is that the engineering design process is partially driven by achieving consensus and reconciling points of view among team members. Characterizing the quality of the design performance by measuring the coherence of the description of related design concepts and events in design documentation is examined. Latent Semantic Analysis (LSA) was used to analyze design documentation written by self-managing, cross-functional engineering design teams. Computational measurements of document variance and textual coherence were applied to the teams' design documents, presentation materials and e-mail communication. The levels of semantic coherence were correlated to assessments by faculty and product designers and engineers from industry of the design teams' process and outcome quality. The results indicated a statistically significant positive correlation between design document coherence and design performance, especially for poorly performing teams. The impact of this research is to provide team managers (people who create teams and manage teams) or self-organizing teams (teams that focus on self-reflection and peer evaluation) computational tools that could be integrated with design information management technologies to assist them in the management of engineering design teams.

Proceedings of the 9th International Detailed Design in Architecture Conference, 2010

The detailed design phase is critical in maintaining the design concept whilst considering aesthetic ventures in light of time, cost, and buildability prior to implementation. During this phase, design components are connected, solutions are tested and methods of implementation finalised. Design becomes a truly interdisciplinary activity. In addition, the challenge of sustainability requires built environment professionals to transcend traditional disciplinary boundaries if effective solutions are to be realised. However, there is currently limited research on how the behaviour of teams affects subsequent products and outcomes. This paper aims to contribute to a better understanding of this link. An experiment was carried out using single discipline and multi-disciplinary teams with differing collective personality characteristics to test whether it is essential to have the right personalities in the design team as well as the correct disciplines. Observation of design workshops provided the necessary data for analysis of how these environments influenced design outcomes. An evolutionary analogy was applied to map and understand the way that ideas behave during each of the four design processes. The teams’ performances and design outcomes are then analysed to draw some tentative conclusions about how design teams may be formed and managed during the detailed design phase.