Research on changes in design has mainly focused on the product domain, which is the manifestation of the design process. This article investigates changes in the process domain, which describes the execution of coordinated and concurrent design activities through interdisciplinary teams. More specifically, this article focuses on changes in the iterative behavior of activities as one of the key levers determining the performance of complex concurrent design processes. In activity network-based models of design processes, the occurrence of such behavior is often expressed probabilistically through iteration-likelihoods. First, the impact of iteration-likelihood changes on the effort and duration of both individual activities and the overall design process is examined through stochastic analysis. Consequently, a method for the investigation of such changes is developed, which grounds on an experimental approach using Monte Carlo simulation of activity network-based process models. The method is applied to the design process of a high-speed machining device for the manufacturing of planetary-ball-bearing housings. This analysis results in a two-dimensional criticality ranking of potential iteration-likelihood changes and in the identification of the most affected individual activities. The article concludes with managerial implications for process planning and improvement and discusses which design activities need to be targeted by project management to prevent and react to critical iteration-likelihood changes.

The planning and scheduling of appropriate resources is essential in engineering design for delivering quality products on time, within cost and at acceptable risk. In order to achieve this, it is necessary to identify and understand the different resources required. This paper attempts to do so through insights drawn from interviews in an aerospace company. Firstly, it investigates what elements have been considered design resources by current modelling approaches and how the approaches have managed resources. Secondly, interviews identified that key design resources does not only include designers but also computational, testing and prototyping resources. Thirdly, the paper introduces resource attributes that can impact on resource availability and their effectiveness on process performance. Fourthly, it proposes a set of requirements to distinguish design resources from company resources. Finally, it advocates for having allocation flexibility to balance all these resources within the process, requiring new approaches for planning and scheduling that can model resources along with their attributes.

The development of models, especially simulation models of both products and processes, has increased in industry and now offer substantial competitive advantages in decision support across many fields. Even so, little is known about the structures of applied modelling processes as the focus so far has primarily been on improving modelling tools and software, methodologies, and modelling outcomes. In this paper, we gain insights into the value creation activities in modelling practice through the analysis of activity structures from 12 different modelling processes across two large UK companies. The results show that modelling process structures can be divided into three distinct process types; ad-hoc modelling for decision support, new model development, and model change management. Existing research mainly considers new model development and therefore it is suggested that the other two types are also part of modelling practice, and therefore should be included in modelling process management. The process types are categorized from a modelling management perspective and a tentative modelling process management toolbox is suggested for further research.

Although modelling tools are intensively used within companies, the modelling process itself is still scarcely researched. The few related works focus on the steps encompassed when developing a model, without taking into consideration the context surrounding it. Nevertheless understanding this context is crucial since this influences the modelling process in terms of objectives, available data and tools. A survey conducted among expert modellers in 1994 provided insights into this context by establishing a profile of the modeller and highlighting the qualities needed to improve modelling practice. However software, technology and businesses have evolved over twenty years, which may have impacted the modelling practice. Twenty years later, we conduct a similar survey. Comparing the results enables studying the evolution of modelling practice over time. The findings are discussed in the light of potentially impacting technological progress and provide insight for future research concerned with improving the modelling process.

Research on changes in design has focused on engineering changes, i.e. changes in the product domain, which is the manifestation of the design process. This article takes a different perspective and investigates changes in the process domain, which is characterised by the coordinated execution of design activities with complex interdependencies. Design process changes (DPCs) comprise various types of perturbations, e.g., delays in activities, changes in customer requirements on design parameters or the addition of new activities to the process plan. This article derives a definition for DPCs, investigates their characteristics, including reasons, types and consequences, and examines existing methods to model and manage DPCs. The research is based on a systematic literature review, which is supported through an on-going industrial case study. Given both the frequent occurrence and potentially severe impacts of DPCs on process performance a set of substantial research gaps are identified and promising directions for future research on DPCs are derived.