The integrated use of enterprise and system dynamics modelling techniques in support of business decisions

Enterprise modelling techniques support business process re-engineering by capturing existing processes and based on perceived outputs, support the design of future process models capable of meeting enterprise requirements. System dynamics modelling tools on the other hand are used extensively for policy analysis and modelling aspects of dynamics which impact on businesses. In this paper, the use of enterprise and system dynamics modelling techniques has been integrated to facilitate qualitative and quantitative reasoning about the structures and behaviours of processes and resource systems used by a Manufacturing Enterprise during the production of composite bearings. The case study testing reported has led to the specification of a new modelling methodology for analysing and managing dynamics and complexities in production systems. This methodology is based on a systematic transformation process, which synergises the use of a selection of public domain enterprise modelling, causal loop and continuous simulationmodelling techniques. The success of the modelling process defined relies on the creation of useful CIMOSA process models which are then converted to causal loops. The causal loop models are then structured and translated to equivalent dynamic simulation models using the proprietary continuous simulation modelling tool iThink

A k-nearest neighbour technique for experience-based adaptation of assembly stations

YesWe present a technique for automatically acquiring operational knowledge on how to adapt assembly systems to new production demands or recover from disruptions. Dealing with changes and disruptions affecting an assembly station is a complex process which requires deep knowledge of the assembly process, the product being assembled and the adopted technologies. Shop-floor operators typically perform a series of adjustments by trial and error until the expected results in terms of performance and quality are achieved. With the proposed approach, such adjustments are captured and their effect on the station is measured. Adaptation knowledge is then derived by generalising from individual cases using a variant of the k-nearest neighbour algorithm. The operator is informed about potential adaptations whenever the station enters a state similar to one contained in the experience base, that is, a state on which adaptation information has been captured. A case study is presented, showing how the technique enables to reduce adaptation times. The general system architecture in which the technique has been implemented is described, including the role of the different software components and their interactions

Focused ion beam milling of brass for microinjection mould fabrication

In this paper focused ion beam (FIB) milling (sputtering) is demonstrated for the fabrication of brass microinjection moulding inserts which have been previously conventionally milled. It is found that FIB milling of the α phase of the material results in much smoother final surfaces than the β phase. An annealing procedure for minimizing the effects of differential sputtering has also been performed. Further with the help of Scanning Electron Microscopy (SEM) and White Light Interferometry (WLI) measurements the FIB milling yield for 70-30 cartridge brass is determined and analysed. Finally, FIB milling of 5µm square trenches with a flat bottom surface is demonstrated

Apparent beam size definition of focused ion beams based on scanning electron microscopy images of nanodots

In this paper the new term apparent beam size of Focused Ion Beam (FIB) is introduced and an original method of its evaluation is demonstrated. Traditional methods of measuring the beam size, like the knife edge method, provide information about the quality of the beam itself but practically they do not give information on the FIB sputtering resolution. To do this, it is necessary to take into account the material dependant interaction of the beam with the specimen and the gas precursor in the vacuum chamber. The apparent beam size can be regarded as the smallest possible dot that FIB can sputter in a given specimen. The method of evaluating it, developed in this paper, is based on the analysis of a series of scanning electron images of FIB produced nanodots. Results show that the apparent beam size can be up to 5 times larger than the actual physical size of the beam and it is significantly influenced by the presence of gas precursor. It is also demonstrated that the apparent beam size can be used as a reference value for optimisation of the beam step during raster scanning

Workpiece Machining Accuracy Prediction Based on Milling Simulation

To ensure the machining accuracy of workpiece, it is necessary to predict the workpiece deformation in machining process through establishing a high precision workpiece deformation forecast model. To solve these problems, a more efficient variable stiffness analysis model is proposed, which can obtain quantitative stiffness value of the machining surface. Applying simulated cutting force in sampling points using finite element analysis software ABAQUS, the single direction variable stiffness rule can be obtained. First of all, finite element simulation model of face milling is established with the Johnson-Cook material model and failure model of 7050 aluminum alloy. Prediction model is established based on SVM and input data is provided by the finite element software ABAQUS simulation. Results show that the model prediction relative error is less than 5%. It is concluded that the effects of milling parameters on workpiece machining deformation and practical guide for production

Learning and reuse of engineering ramp-up strategies for modular assembly systems

YesWe present a decision-support framework for speeding up the ramp-up of modular assembly systems by learning from past experience. Bringing an assembly system to the expected level of productivity requires engineers performing mechanical adjustments and changes to the assembly process to improve the performance. This activity is time-consuming, knowledge-intensive and highly dependent on the skills of the engineers. Learning the ramp-up process has shown to be effective for making progress faster. Our approach consists of automatically capturing information about the changes made by an operator dealing with disturbances, relating them to the modular structure of the machine and evaluating the resulting system state by analysing sensor data. The feedback thus obtained on applied adaptations is used to derive recommendations in similar contexts. Recommendations are generated with a variant of the k-nearest neighbour algorithm through searching in a multidimensional space containing previous system states. Applications of the framework include knowledge transfer among operators and machines with overlapping structure and functionality. The application of our method in a case study is discussed.Funded by the European Commission as part of the 7th Framework Program under the Grant agreement CP-FP 229208-2, FRAME project

Redesign methodology for mechanical assembly

Design for assembly is the concept of carrying out critical thought early in the design stage to create assembly easement at the production stage. In the aerospace industry, products have very long lives, frequently being optimised rather than introducing new products. This has meant older products, which are stable income generators, have not benefited from the latest design for assembly methods and manufacturing technology suffers from obsolescence. It has been established that a large percentage of overall product cost is determined at the design stage; thus, existing products suffer from preloaded costs. This paper takes existing design for assembly methodologies and analyses them with respect to the unique challenges involved in legacy product redesign. Several novel factors that contribute to redesign analysis are identified such obsolescence impact and a holistic operation difficulty assessment. A tool is developed to identify potential redesign for assembly projects. The tool is demonstrated through the application of real data and comparing against business decisions. The tool was found to provide a strong indication of where profitable projects may be launched

Conceptual framework for ubiquitous cyber-physical assembly systems in airframe assembly

Current sectoral drivers for the manufacturing of complex products - such as airframe assembly -require new manufacturing system paradigms to meet them. In this paper, we propose a conceptual framework for cyber-physical systems driven by ubiquitous context-awareness by drawing together a unique and coherent vision that merges several extant concepts. This framework leverages recent progress in agent-based systems, exible manufacturing, ubiquitous computing, and metrology-driven robotic assembly in the Evolvable Assembly Systems project. As such, although it is adapted for and grounded in manufacturing facilities for airframe assembly, it is not specifically tailored to that application and is a much more general framework. As well as outlining our conceptual framework, we also provide a vision for assembly grounded in a review of existing research in the area

A Learning Method for Automated Disassembly

While joining tolerances, and therefore forces, are known in the assembly process, the determination of disassembly forces is not possible. This is caused by changes in the product properties during the product operation, which has multiple reasons such as thermal or mechanical stress on the product. Regarding the planning of disassembly tasks, disassembly times and tools cannot be planned properly. They have to be determined in the process or stay undefined, which can result in damaging of the product. This article shows an approach to describe the necessary disassembly forces without having to investigate the complex physical influences caused by the usage of the product. To do so, a Learning Method is developed, which is sustained by a Lookup-Table for the estimation of disassembly forces based on basic input data such as hours of operation and operating characteristics. Missing values will be interpolated by using multiple linear regression. The concept will be illustrated in the example of a turbine blade connection

Common shared system model for evolvable assembly systems

A vital aspect of distributed control in an adaptable production system is coherence between each system resource. The Evolvable Assembly Systems project addresses this challenge using a common shared system model. This paper provides an overview of the project and the shared system model approach as implemented in a real world demonstration cell