The reality of design process planning

Most companies struggle with the efficiency of their processes. One contributory factor is the lack of efficient process planning. This paper describes current planning practise in industry, which uses a multitude of different plans in parallel. The units of planning and their resulting plans roughly fall into product plans considering cost, bill of material and procurement considerations; process plans including different milestone, task and activity plans and quality plans. This paper maps out the ownership of these plans, and establishes that organisations work because individuals use more then one plan and have a tacit understanding of the relationships between these plans. The lack of effective plans affects the company through a lack of understanding of process connectivity and in consequence bad communication

Towards a change process planning tool

The relationship between a product and its design process is generally complex and not fully understood. When modifying a product, industry still rarely considers the implementation process and its consequences for other design activities in the company, which is hard to assess with conventional planning methods. Although change processes are highly constrained, product and process constraints are not usually considered together or traded off against each other when planning the change. Inadequate assessment and planning of the change implementation process can lead to costly knock-on effects across the product and the design process. This paper argues for a combination of change and process research and discusses requirements for a change process planning tool. It proposes a system for the analysis of the impact of change on the product as well as other company activities. Then, a more informed selection between change alternatives is possible

Galaxy correlations and the BAO in a void universe: structure formation as a test of the Copernican Principle

A suggested solution to the dark energy problem is the void model, where accelerated expansion is replaced by Hubble-scale inhomogeneity. In these models, density perturbations grow on a radially inhomogeneous background. This large scale inhomogeneity distorts the spherical Baryon Acoustic Oscillation feature into an ellipsoid which implies that the bump in the galaxy correlation function occurs at different scales in the radial and transverse correlation functions. We compute these for the first time, under the approximation that curvature gradients do not couple the scalar modes to vector and tensor modes. The radial and transverse correlation functions are very different from those of the concordance model, even when the models have the same average BAO scale. This implies that if void models are fine-tuned to satisfy average BAO data, there is enough extra information in the correlation functions to distinguish a void model from the concordance model. We expect these new features to remain when the full perturbation equations are solved, which means that the radial and transverse galaxy correlation functions can be used as a powerful test of the Copernican Principle.Comment: 12 pages, 8 figures, matches published versio

The spiral of applied research: A methodological view on integrated design research

Abstract not available

Model granularity and related concepts

Models are integral to engineering design and basis for many decisions. Therefore, it is necessary to comprehend how a model’s properties might influence its behaviour. Model granularity is an important property but has so far only received limited attention. The terminology used to describe granularity and related phenomena varies and pertinent concepts are distributed across communities. This article positions granularity in the theoretical background of models, collects formal definitions for relevant terms from a range of communities and discusses the implications for engineering design

Parameter trails

Successful communication is vital for the success of any design project. However, communication often fails, adversely affecting design process efficiency and product quality.understand the connections between different aspects of design and don–t know where to find out more information or who to talk to. This paper presents a new model, developed from current project planning techniques, which supports communication using parameter-specific data. It enables designers to question information, inform their colleagues pro-actively and assess the impact of changing parameter values on subsequent design tasks. Such interaction is critical in allowing designers to see how their own tasks fit into the overall product design

A functional analysis of change propagation

A thorough understanding of change propagation is fundamental to effective change management during product redesign. A new model of change propagation, as a result of the interaction of form and function is presented and used to develop an analysis method that determines how change is likely to propagate. The analysis produces a Design Structure Matrix, which clearly illustrates change propagation paths and highlights connections that could otherwise be ignored. This provides the user with an in-depth knowledge of product connectivity, which has the potential to support the design process and reduce the product's susceptibility to future change

Randomized Extended Kaczmarz for Solving Least-Squares

We present a randomized iterative algorithm that exponentially converges in expectation to the minimum Euclidean norm least squares solution of a given linear system of equations. The expected number of arithmetic operations required to obtain an estimate of given accuracy is proportional to the square condition number of the system multiplied by the number of non-zeros entries of the input matrix. The proposed algorithm is an extension of the randomized Kaczmarz method that was analyzed by Strohmer and Vershynin.Comment: 19 Pages, 5 figures; code is available at https://github.com/zouzias/RE

Experimental Investigation of the Implications of Model Granularity for Design Process Simulation

Determining a suitable level of description, or granularity, for a product or process model is not straightforward, especially since granularity can manifest in multiple ways, but it is important to capture important elements in the model without building models that are too large to understand. This article investigates the implications of model granularity choices by simulating the design process of a diesel engine on different levels of detail, comparing the results and exploring ways to account for the differences. It uses two Design Structure Matrix (DSM) models for change prediction in a diesel engine at different levels of granularity to run simulations of the design process. Changes are a major source of rework and lead to frequent rescheduling of design tasks. The incremental nature of product development as well as design changes and their propagation complicate design process planning further. Process simulation may provide support in such contexts when it is based on an appropriate description of the product. The article shows that while coarse models can give an indication of likely process behavior, they miss potentially significant iteration loops.</jats:p