Volatiles from biofumigant plants have a direct effect on carpogenic germination of sclerotia and mycelial growth of Sclerotinia sclerotiorum

Aims Sclerotia of Sclerotinia sclerotiorum survive in soil and germinate to produce apothecia which release airborne ascospores. Current control methods rely predominantly on the use of fungicides to kill ascospores. The aim of this research was to identify potential biofumigation treatments which suppress sclerotial germination, providing a potential alternative and long-term approach to disease management. Methods Microcosm and in vitro experiments were conducted using dried and milled plant material from six different biofumigant crop plants to determine effects on carpogenic germination of sclerotia and mycelial growth of S. sclerotiorum. Results All biofumigant plants significantly reduced germination of S. sclerotiorum sclerotia in the microcosm experiments, but were less effective against larger sclerotia. In vitro experiments showed a direct effect of biofumigant volatiles on both the mycelial growth of S. sclerotiorum, and carpogenic germination of sclerotia, where the most effective treatment was B. juncea ‘Vittasso’. Conclusions It was clear from this study that biofumigant crop plants have potential as part of an integrated disease management system for control of S. sclerotiorum. The microcosm experiments described here provide a straightforward and reliable screening method for evaluating different biofumigants for activity

Internal and External Involvements in Integrated Product Development: A Two-Step Clustering Approach

© 2017 The Authors. The term Integrated Product Development (IPD) has been introduced as a focus for cross-disciplinary research and can have several forms, or manifestations, with regard to the existing disciplines such as concurrent engineering and design for manufacturing. Of central importance to IPD is the interpretation of the term "integration", particularly with regard to internal and external elements. However, there is not yet an explicit understanding of an appropriate degree of integration, or involvement, with respect to its different forms, that can assure successful implementation of IPD frameworks in practice. Through a review and clustering of the literature, this paper aims to address this challenge

Risk across design domains

Design processes involve risk: to life and limb if the product is unsafe, to the financial health of the company if the product is late, unsuccessful or simply the wrong product, as well as to the emotions and careers of the designers. Many of the risks are shared universally by all designers, but each different industry and each different project faces its own spectrum of serious and minor risks. Different industries have put their methodological effort into finding ways to mitigate the risks they recognise as important. As part of the Across Design project exploring similarities and differences between design processes in different industries, this paper examines how risks are perceived and handled in different types of design process, and proposes that designers and managers can usefully look to other industries for ways to handle risks that are more central for those other industries

Efficient optimisation of structures using tabu search

This paper presents a novel approach to the optimisation of structures using a Tabu search (TS) method. TS is a metaheuristic which is used to guide local search methods towards a globally optimal solution by using flexible memory cycles of differing time spans. Results are presented for the well established ten bar truss problem and compared to results published in the literature. In the first example a truss is optimised to minimise mass and the results compared to results obtained using an alternative TS implementation. In the second example, the problem has multiple objectives that are compounded into a single objective function value using game theory. In general the results demonstrate that the TS method is capable of solving structural optimisation problems at least as efficiently as other numerical optimisation approaches

Towards the Design of Resilient Large-scale Engineering Systems

Resilience has mostly been thought of as the ability to recover from adversity. However, it is now increasingly recognised that resilience should not only serve as a means for organisations to survive hardship, but also to thrive and prosper. For large-scale engineering systems, such as telecommunications networks and power grids, this is vital due to relatively long life cycles leading to large uncertainties, and also due to the significant investments involved. Exactly how this and thus resilience should be designed into such systems, however, is less well defined. Here, the term resilience is explored through engineering, organisational and ecological literature to understand differing perspectives from select domains before distilling these into the three engineering design lifecycle properties: robustness, adaptability and flexibility. In particular, a distinction is highlighted between adaptability and flexibility following findings in literature. These properties and the concept of resilience are discussed with reference to system performance in order to serve as requirements for designing large-scale resilient engineering systems

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

Characteristics of changeable systems across value chains

Engineering changes (ECs) are inevitable for businesses due to increasing innovation, shorter lifecycles, technology and process improvements and cost reduction initiatives. The ECs could propagate and cause further changes due to existing system dependencies, which can be challenging. Hence, change management (CM) is a relevant discipline, which aims to reduce the impact of changes. EC assessment methods form the basis of CM that support in assessing system dependencies and the impact of changes. However, there is limited understanding of which factors influence the change-ability across value chains (VCs). This research adopted a VC approach to EC assessment. Dependencies in products and processes were captured, followed by the risk (i.e. likelihood x impact) assessment of ECs using change prediction method (CPM). Four case studies were conducted from two industries (automotive, furniture) to identify design (product) and manufacturing (process) elements with high risk to be affected by ECs. Based on the case results, characteristics were identified that influence change-ability across VC. This contributed to the CM domain while businesses could also use the results to assess ECs across VC, and improve the design of products and processes by increasing their changeability across VC e.g. by proactive decoupling or reactive handling of system dependencies.Department for Business, Energy and Industrial Strategy (BEIS), UK under Advanced Manufacturing Supply Chain Initiative (AMSCI