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This paper aims to present the mathematical foundation of so-called advance algorithms, developed to compensate for defects during acceleration and deacceleration of the print head in filament-based melt extrusion additive processes. It then investigates the validity of the mathematical foundation, its performance on a low-cost system and the effect of changing layer height on the algorithm’s associated process parameter.

This study starts with a compilation and review of literature associated with advance algorithms, then elaborates on its mathematical foundation and methods of implementation. Then an experiment displaying the performance of the algorithm implemented in Marlin machine firmware, Linear Advance 1.0, is performed using three different layer heights. The results are then compared with simulations of the system using Simulink.

Findings suggests that advance algorithms following the presented approach is capable of eliminating defects because of acceleration and deacceleration of the print head. The results indicate a layer height dependency on the associated process parameter, requiring higher compensation values for lower layer heights. It also shows higher compensation values for acceleration than deacceleration. Results from the simulated mathematical model correspond well with the experimental results but predict some rapid variations in flow rate that is not reflected in the experimental results.

As there are large variations in printer design and materials, deviation between different setups must be expected.

To the best of authors’ knowledge, this study is the first to describe and investigate advance algorithms in academic literature.

This paper proposes the combination of rapid prototyping and physical modelling as a set-based concept evaluation method in the early stage of new product development.

The concept evaluation method is applied in a case study of a new metal additive manufacturing process for aluminium, where a set of four extruder concepts has been modelled and evaluated. Rapid prototyping was used to produce plastic models of the different designs, and plasticine feedstock material was used to physically model the metal flow during operation. Finally, the selected concept has been verified in full-scale for processing of aluminium feedstock material.

The proposed method led to several valuable insights on critical factors that were unknown at the outset of the development project. Overall, these insights enabled concept exploration and concept selection that led to a substantially better solution than the original design.

This method can be applied for other projects where numerical approaches are not applicable or capable, and where the costs or time required for producing full-scale prototypes are high.

Employing this method can enable a more thorough exploration of the design space, allowing new solutions to be discovered.

The proposed method allows a design team to test and evaluate multiple concepts at lower cost and time than what is usually required to produce full-scale prototypes. It is, therefore, concluded to be a valuable design strategy for the early development stages of complex products or technologies.

Most complex engineering projects encounter unexpected events through their life cycle. These are traditionally attributed to inaccurate foresight and poor planning. Outlining a nonanticipatory alternate, the authors seek to explain the ability to rebound from unexpected events, without foresight, using resilient systems theory. This paper seeks to outline the theoretical underpinnings of project resilience and to identify criteria for planning and selecting projects for greater resilience.

Investigating project resilience, this paper studies the relationship between unexpected events and project performance in 21 projects. The authors perform a systematic review of project ex post evaluations 3–12 years after project completion.

First, the authors find that all projects encountered unexpected events, even when discounting planning error. Second, the authors show that, as a consequence, projects underperformed, not necessarily relative to formal criteria, but in terms of subjective opportunity cost, that is, relative to competing alternates – known or imagined – foregone by their implementation. Finally, the authors identify four types of resilient projects – superior, equivalent, compensatory and convertible projects – as opportunities for building project resilience.

The properties of resilient projects provide opportunities for building resilience in complex projects.

Departing from traditional efforts to “de risk” plans and “de-bias” planners, this paper focuses on the properties of projects themselves, as an alternate to improved foresight and up-front planning.

The aim of this paper is to suggest a redefinition of the functional product value calculation in lean product development (LPD). The proposed method integrates emotional customer value into the traditional model, which is based on minimizing operating costs and reducing time‐to‐market.

Perceptions of customer value among employees at a Norwegian boat manufacturer, customers, and competitors are investigated through a case study. Results are compared with principles for promoting value and minimizing waste in LPD.

Findings from the case study suggest that a less‐than‐perfect match between customer needs and product offerings sometimes improves customer satisfaction. Furthermore, how customers perceive product value depends on experience that may be at variance with current needs. It is also suggested that deep understanding of customer‐defined value does not imply an ability to satisfy that value.

Understanding the position of meaning‐driven and technology‐driven innovation in different types of industries represents a challenge for further research, as does the issue of whether these two are the only dimensions driving a sustainable innovation strategy. Actionable knowledge on how emotional value can be maximized is also needed.

Maximizing customer value is a core principle in LPD, but the value definitions used tend to be based on logical reasoning rather than real‐life observations. This article presents empirical insights concerning different stakeholders' perceptions of customer value, and the resulting implications for the present lean framework.