A methodology for near net shape process feasibility assessment

Manufacturing engineers are frequently asked to select the best process for creating components but often the judgement is qualitative rather than quantitative. This paper presents a methodology (DCFA – Differential Cost and Feasibility Analysis) for assessing the technological and economic feasibility of using Near Net Shape (NNS) processes for the manufacturing of specific components. The methodology examines changes in raw material usage and finish processes (e.g. machining processes) that would result from adaption of a new manufacturing process. To illustrate the method, a case study that assesses the feasibility of using centrifugal casting for the production of valve cages is detailed. The case study concludes that the application of this process to the current manufacturing lines could result in significant cost reductions (particularly in machining time and reduction of scrappage). The feasibility methodology is generic and can potentially be used to investigate the application of a broad range of NNS processes in general manufacturing applications. Further, the developed cost models also allow the economic impact of a new process to be assessed, even at the early stages of product design

Gaussian quantum Monte Carlo methods for fermions

We introduce a new class of quantum Monte Carlo methods, based on a Gaussian quantum operator representation of fermionic states. The methods enable first-principles dynamical or equilibrium calculations in many-body Fermi systems, and, combined with the existing Gaussian representation for bosons, provide a unified method of simulating Bose-Fermi systems. As an application, we calculate finite-temperature properties of the two dimensional Hubbard model.Comment: 4 pages, 3 figures, Revised version has expanded discussion, simplified mathematical presentation, and application to 2D Hubbard mode

Concurrent optimization of process parameters and product design variables for near net shape manufacturing processes

This paper presents a new systematic approach to the optimization of both design and manufacturing variables across a multi-step production process. The approach assumes a generic manufacturing process in which an initial Near Net Shape (NNS) process is followed by a limited number of finishing operations. In this context the optimisation problem becomes a multi-variable problem in which the aim is to optimize by minimizing cost (or time) and improving technological performances (e.g. turning force). To enable such computation a methodology, named Conditional Design Optimization (CoDeO) is proposed which allows the modelling and simultaneous optimization of process parameters and product design (geometric variables), using single or multi-criteria optimization strategies. After investigation of CoDeO’s requirements, evolutionary algorithms, in particular Genetic Algorithms, are identified as the most suitable for overall NNS manufacturing chain optimization The CoDeO methodology is tested using an industrial case study that details a process chain composed of casting and machining processes. For the specific case study presented the optimized process resulted in cost savings of 22% (corresponding to equivalent machining time savings) and a 10% component weight reduction

Process selection methodology for near net shape manufacturing

This paper presents a new selection methodology that for the first time supports the identification of Near Net Shape (NNS) processes. The methodology, known as "Product, Geometry, Manufacturing and Materials Matching" (ProGeMa3), is composed of four steps, which aim to minimize raw material usage and machining by adopting a NNS approach. A key component of the methodology is the Process Selection Matrix (ProSMa) that associates a component’s shape and production volume with its material requirements to reduce the number of candidate NNS processes. A final selection is then made from this shortlist by using fuzzy logic and considering other constraints and functional requirements. The ProGeMa3 selection process is illustrated by its application to an industrial component that resulted in changes to the processes used for its commercial manufacture. The ProGeMa3 and ProSMa presented in this paper aspires to be current and comprehensive for solid metallic components produced by casting, forging and additive technologies. However, ProSMa is also accessible as an open source resource available for other researcher to extend and adapt

Outsourcing labour to the cloud

Various forms of open sourcing to the online population are establishing themselves as cheap, effective methods of getting work done. These have revolutionised the traditional methods for innovation and have contributed to the enrichment of the concept of 'open innovation'. To date, the literature concerning this emerging topic has been spread across a diverse number of media, disciplines and academic journals. This paper attempts for the first time to survey the emerging phenomenon of open outsourcing of work to the internet using 'cloud computing'. The paper describes the volunteer origins and recent commercialisation of this business service. It then surveys the current platforms, applications and academic literature. Based on this, a generic classification for crowdsourcing tasks and a number of performance metrics are proposed. After discussing strengths and limitations, the paper concludes with an agenda for academic research in this new area

The use of non-intrusive user logging to capture engineering rationale, knowledge and intent during the product life cycle

Within the context of Life Cycle Engineering it is important that structured engineering information and knowledge are captured at all phases of the product life cycle for future reference. This is especially the case for long life cycle projects which see a large number of engineering decisions made at the early to mid-stages of a product's life cycle that are needed to inform engineering decisions later on in the process. A key aspect of technology management will be the capturing of knowledge through out the product life cycle. Numerous attempts have been made to apply knowledge capture techniques to formalise engineering decision rationale and processes; however, these tend to be associated with substantial overheads on the engineer and the company through cognitive process interruptions and additional costs/time. Indeed, when life cycle deadlines come closer these capturing techniques are abandoned due the need to produce a final solution. This paper describes work carried out for non-intrusively capturing and formalising product life cycle knowledge by demonstrating the automated capture of engineering processes/rationale using user logging via an immersive virtual reality system for cable harness design and assembly planning. Associated post-experimental analyses are described which demonstrate the formalisation of structured design processes and decision representations in the form of IDEF diagrams and structured engineering change information. Potential future research directions involving more thorough logging of users are also outlined

Near net shape manufacturing of metal : a review of approaches and their evolutions

In the last thirty years the concept of manufacturability has been applied to many different processes in numerous industries. This has resulted in the emergence of several different "Design for Manufacturing" methodologies which have in common the aim of reducing productions costs through the application of general manufacturing rules. Near net shape technologies have expanded these concepts, targeting mainly primary shaping process, such as casting or forging. The desired outcomes of manufacturability analysis for near-net-shape (NNS) processes are cost and lead/time reduction through minimization of process steps (in particular cutting and finishing operations) and raw material saving. Product quality improvement, variability reduction and component design functionality enhancement are also achievable through NNS optimization. Process parameters, product design and material selection are the changing variables in a manufacturing chain that interact in complex, non-linear ways. Consequently modeling and simulation play important roles in the investigation of alternative approaches. However defining the manufacturing capability of different processes is also a “moving target” because the various NNS technologies are constantly improving and evolving so there is challenge in accurately reflecting their requirements and capabilities. In the last decade, for example, CAD, CNC technologies and innovation in materials have impacted enormously on the development of NNS technologies. This paper reviews the different methods reported for NNS manufacturability assessment and examines how they can make an impact on cost, quality and process variability in the context of a specific production volume. The discussion identifies a lack of structured approaches, poor connection with process optimization methodologies and a lack of empirical models as gaps in the reported approaches

A methodology for assessing the feasibility of producing components by flow forming

This paper describes a methodology for assessing the applicability of the flow forming process for the manufacture of specific components. The process starts by filtering potential candidates for flow forming from a component collection (e.g. company catalogue) and then carries out a detailed assessment of quantitative, technological and economic feasibility before determining a viable process plan. The process described uses analytical relationships and empirical criteria drawn from the literature.. A process time model (based on an analogy with CNC turning) is used to develop a hybrid cost model in order to evaluate economic feasibility. The paper concluded with a brief summary of the results of applying the process to an industrial case study

Automated knowledge capture in 2D and 3D design environments

In Life Cycle Engineering, it is vital that the engineering knowledge for the product is captured throughout its life cycle in a formal and structured manner. This will allow the information to be referred to in the future by engineers who did not work on the original design but are wanting to understand the reasons that certain design decisions were made. In the past, attempts were made to try to capture this knowledge by having the engineer record the knowledge manually during a design session. However, this is not only time-consuming but is also disruptive to the creative process. Therefore, the research presented in this paper is concerned with capturing design knowledge automatically using a traditional 2D design environment and also an immersive 3D design environment. The design knowledge is captured by continuously and non-intrusively logging the user during a design session and then storing this output in a structured eXtensible Markup Language (XML) format. Next, the XML data is analysed and the design processes that are involved can be visualised by the automatic generation of IDEF0 diagrams. Using this captured knowledge, it forms the basis of an interactive online assistance system to aid future users who are carrying out a similar design task