Impact of composite manufacturing constraints on aerospace stiffened panel design

This paper reports on a design study assessing the impact of laminate manufacturing constraints on the structural performance and weight of composite stiffened panels. The study demonstrates that maximizing ply continuity results in weight penalties, while various geometric constraints related to manufacture and repair can be accommodated without significant weight penalties, potentially generating robust flexible designs.

The prediction of process-induced deformation in a thermoplastic composite in support of manufacturing simulation

Digital manufacturing techniques can simulate complex assembly sequences using computer-aided design-based, as-designed' part forms, and their utility has been proven across several manufacturing sectors including the ship building, automotive and aerospace industries. However, the reality of working with actual parts and composite components, in particular, is that geometric variability arising from part forming or processing conditions can cause problems during assembly as the as-manufactured' form differs from the geometry used for any simulated build validation. In this work, a simulation strategy is presented for the study of the process-induced deformation behaviour of a 90 degrees, V-shaped angle. Test samples were thermoformed using pre-consolidated carbon fibre-reinforced polyphenylene sulphide, and the processing conditions were re-created in a virtual environment using the finite element method to determine finished component angles. A procedure was then developed for transferring predicted part forms from the finite element outputs to a digital manufacturing platform for the purpose of virtual assembly validation using more realistic part geometry. Ultimately, the outcomes from this work can be used to inform process condition choices, material configuration and tool design, so that the dimensional gap between as-designed' and as-manufactured' part forms can be reduced in the virtual environment.

An audit of drug shortages in a community pharmacy practice

Background: There are no firm data on drug shortages in Irish community pharmacy. This prospective observational study aimed to characterise the drug shortage problem in an Irish community pharmacy.
Aims: The primary aim was to determine numbers and durations of drug shortages. Secondary aims included comparing these shortages with Irish Pharmacy Union (IPU) drug shortage lists and determining the frequency with which notifications were received prior to shortages. Further secondary aims were to examine relationships between causes of drug shortages and drug costs and between causes of drug shortages and shortage durations.
Methods: The study took place in a community pharmacy in a Limerick City suburb between October 2012 and February 2013. Data were collected daily regarding drugs that were dispensed, but unavailable to purchase. Suppliers/manufacturers provided data on the reasons for shortages.
Results: 65/1,232 dispensed drugs (5.3 %) were in short supply over the study period. Median shortage duration was 13 days (interquartile range 4–32 days) and median cost was €8.10. Numbers of unavailable drugs by month varied from 13 to 38. Monthly IPU drug shortage lists identified between six and eight of these shortages depending on the month. Two notifications were received from suppliers/manufacturers regarding shortages. Parallel exports had the highest mean costs (mean €38.05) and manufacturing problems were associated with the longest durations (mean 57.44 days).
Conclusions: This study highlights the drug shortage problem in an Irish community pharmacy. We propose that enhanced communication between all stakeholders is the most worthwhile solution. Further studies are needed.

The Development of an Immersive Virtual Reality Environment for Manufacturing and Improving Organizational Learning

This paper examines the applicability of an immersive virtual reality (VR) system to the process of organizational learning in a manufacturing context. The work focuses on the extent to which realism has to be represented in a simulated product build scenario in order to give the user an effective learning experience for an assembly task. Current technologies allow the visualization and manipulation of objects in VR systems but physical behaviors such as contact between objects and the effects of gravity are not commonly represented in off the shelf simulation solutions and the computational power required to facilitate these functions remains a challenge. This work demonstrates how physical behaviors can be coded and represented through the development of more effective mechanisms for the computer aided design (CAD) and VR interface.

Automated Methods for Aircraft Design Integrated with Manufacturing

Aircraft design is a complex, long and iterative process that requires the use of various specialties and optimization tools. However these tools and specialities do not include manufacturing, which is often considered later in the product development process leading to higher cost and time delays. This work focuses on the development of an automated design tool that accounts for manufacture during the design process focusing on early geometry definition which in turn informs assembly planning. To accomplish this task the design process needs to be open to any variation in structural configuration while maintaining the design intent. Redefining design intent as a map which links a set of requirements to a set of functions using a numerical approach enables the design process itself to be considered as a mathematical function. This definition enables the design process to utilise captured design knowledge and translate it into a set of mathematical equations that design the structure. This process is articulated in this paper using the structural design and definition for an aircraft fuselage section as an exemplar.

Prediction of integral type failures in semiconductor manufacturing through classification methods

Smart management of maintenances has become fundamental in manufacturing environments in order to decrease downtime and costs associated with failures. Predictive Maintenance (PdM) systems based on Machine Learning (ML) techniques have the possibility with low added costs of drastically decrease failures-related expenses; given the increase of availability of data and capabilities of ML tools, PdM systems are becoming really popular, especially in semiconductor manufacturing. A PdM module based on Classification methods is presented here for the prediction of integral type faults that are related to machine usage and stress of equipment parts. The module has been applied to an important class of semiconductor processes, ion-implantation, for the prediction of ion-source tungsten filament breaks. The PdM has been tested on a real production dataset. © 2013 IEEE.