A new paradigm in large-scale assembly-research priorities in measurement assisted assembly

This paper presents for the first time the concept of measurement assisted assembly (MAA) and outlines the research priorities of the realisation of this concept in the industry. MAA denotes a paradigm shift in assembly for high value and complex products and encompasses the development and use of novel metrology processes for the holistic integration and capability enhancement of key assembly and ancillary processes. A complete framework for MAA is detailed showing how this can facilitate a step change in assembly process capability and efficiency for large and complex products, such as airframes, where traditional assembly processes exhibit the requirement for rectification and rework, use inflexible tooling and are largely manual, resulting in cost and cycle time pressures. The concept of MAA encompasses a range of innovativemeasurement- assisted processes which enable rapid partto- part assembly, increased use of flexible automation, traceable quality assurance and control, reduced structure weight and improved levels of precision across the dimensional scales. A full scale industrial trial of MAA technologies has been carried out on an experimental aircraft wing demonstrating the viability of the approach while studies within 140 smaller companies have highlighted the need for better adoption of existing process capability and quality control standards. The identified research priorities for MAA include the development of both frameless and tooling embedded automated metrology networks. Other research priorities relate to the development of integrated dimensional variation management, thermal compensation algorithms as well as measurement planning and inspection of algorithms linking design to measurement and process planning. © Springer-Verlag London 2013.

Research on reliability evaluation of reconfigurable manufacturing system

It is a crucial task to evaluate the reliability of manufacturing process in product development process. Process reliability is a measurement of production ability of reconfigurable manufacturing system (RMS), which serves as an integrated performance indicator of the production process under specified technical constraints, including time, cost and quality. An integration framework of manufacturing process reliability evaluation is presented together with product development process. A mathematical model and algorithm based on universal generating function (UGF) is developed for calculating the reliability of manufacturing process with respect to task intensity and process capacity, which are both independent random variables. The rework strategies of RMS are analyzed under different task intensity based on process reliability is presented, and the optimization of rework strategies based on process reliability is discussed afterwards.

How do engineering students develop practical competencies during a period of industrial placement? - Students' perceptions

This paper explores engineering students' perceptions of developing practical competencies as experienced in their industrial placements. In addition, it discusses the criticisms in the literature on Problem Based Learning, Project Based Learning and Conceive-Design-Implement-Operate in relation to the evaluation of effective learning and teaching during placements. The paper goes on to discuss a study which examines how undergraduate engineering students develop practical competencies during their industrial placements. A phenomenological research approach is adopted using in-depth interviews and document analysis. The research findings from this PhD study will contribute to the knowledge, theory and practice for the students, the industries and the institutions of higher education as students' practical competencies are developed and graduate employability rises. In conclusion, this study explores students' experiences of developing practical competencies during industrial placements. Hence, the study should be able to contribute to a set of evidence-based guidelines for higher education institutions and industry.

A European competence framework for industrial pharmacy practice in biotechnology

Project Report: The PHAR-IN ("Competences for industrial pharmacy practice in biotechnology") looked at whether there is a difference in how industrial employees and academics rank competences for practice in the biotechnological industry. A small expert panel consisting of the authors of this paper produced a biotechnology competence framework by drawing up an initial list of competences then ranking them in importance using a three-stage Delphi process. The framework was next evaluated and validated by a large expert panel of academics (n = 37) and industrial employees (n = 154). Results show that priorities for industrial employees and academics were similar. The competences for biotechnology practice that received the highest scores were mainly in: . "Research and Development", . "Upstream" and "Downstream" Processing', " . "Product development and formulation", " . "Aseptic processing", ."Analytical methodology", . "Product stability", and . "Regulation". The main area of disagreement was in the category "Ethics and drug safety" where academics ranked competences higher than did industrial employees.

Comparative performance between two photogrammetric systems and a reference laser tracker network for large-volume industrial measurement

This paper determines the capability of two photogrammetric systems in terms of their measurement uncertainty in an industrial context. The first system – V-STARS inca3 from Geodetic Systems Inc. – is a commercially available measurement solution. The second system comprises an off-the-shelf Nikon D700 digital camera fitted with a 28 mm Nikkor lens and the research-based Vision Measurement Software (VMS). The uncertainty estimate of these two systems is determined with reference to a calibrated constellation of points determined by a Leica AT401 laser tracker. The calibrated points have an average associated standard uncertainty of 12·4 μm, spanning a maximum distance of approximately 14·5 m. Subsequently, the two systems’ uncertainty was determined. V-STARS inca3 had an estimated standard uncertainty of 43·1 μm, thus outperforming its manufacturer's specification; the D700/VMS combination achieved a standard uncertainty of 187 μm.