Cost model development using virtual manufacturing and data mining: part I—methodology development

This paper reports on research, the aim of which has been to investigate the use of virtual manufacturing and data mining techniques to automate the identification of manufacturing process time estimating relationships that form the basis of product and process cost models. Such models provide information that is critical to all stages of the product development process and to ensuring that development of cost-effective product design and production methods. Use of virtual manufacturing models and data mining techniques enables the majority of the activities involved in the cost model development process to be automated. Hence, reducing the time and effort required, reducing the current high level of reliance on expert judgment and enabling higher levels of cost detail to be estimated. The research reported, therefore, focuses on the use of virtual manufacturing to generate datasets which are then analysed using data mining to identify suitable cost models for manufacturing processes. Part I, of this two-part paper, describes the development of a model development methodology that makes use of virtual manufacturing models and data mining techniques and uses case study data to validate this methodology. Part II will then examine in detail the effectiveness of alternative data mining algorithms in terms of their ability to develop relationships that are (1) representative of the real causal relationships that exist and (2) provide a high level of estimating accuracy.     

Planning for integration — a data oriented approach

To achieve succesful integration in a CIM environment the planning process should be based on a data oriented approach. This involves the construction of a strategic data model which shows the key entities and data relationships within the organization. Through the identification of business objectives, and the application systems which support them, the data model provides a stable foundation on which to build an integrated environment. Fundamental to the planning process is the premise that a data model is stable whilst application processes are volatile and indeed should be designed to be flexible.     

An association rule mining and maintaining approach in dynamic database for aiding product–service system conceptual design

Many previous researches on high-speed machining have been conducted to pursue high machining efficiency and accuracy. In the present study, the characteristics of cutting forces, surface roughness, and chip formation obtained in high and ultra high-speed face milling of AISI H13 steel (46–47 HRC) are experimentally investigated. It is found that the ultra high cutting speed of 1,400?m/min can be considered as a critical value, at which relatively low mechanical load, good surface finish, and high machining efficiency are expected to arise at the same time. When the cutting speed adopted is below 1,400?m/min, the contribution order of the cutting parameters for surface roughness Ra is axial depth of cut, cutting speed, and feed rate. As the cutting speed surpasses 1,400?m/min, the order is cutting speed, feed rate, and axial depth of cut. The developing trend of the surface roughness obtained at different cutting speeds can be estimated by means of observing the variation of the chip shape and chip color. It is concluded that when low feed rate, low axial depth of cut, and cutting speed below 1,400?m/min are adopted, surface roughness Ra of the whole machined surface remains below 0.3?μm, while cutting speed above 1,400?m/min should be avoided even if the feed rate and axial depth of cut are low.     

Reliability-based design optimization of a pick-up device of a manganese nodule pilot mining robot using the Coandă effect

Design of a pick-up device using the Coandă effect in a deep-sea mining robot is vital to develop a reliable and sustainable deep-sea mining system. One of the crucial performance metrics of this device is the collection efficiency since it affects the mining efficiency of the entire system. However, the collection efficiency is significantly affected by the uncertainties of shape, size and mass of manganese nodules on the seabed. In this study, reliability-based design optimization (RBDO) was performed to improve the reliability of the collection efficiency of the pick-up device under these environmental uncertainties. First, a computational model based on the Coandă effect that predicts the collection efficiency of the pick-up device was developed. Next, RBDO based on the Akaike information criterion method was employed to design the pick-up device by using this model. The results demonstrated that the proposed design methodology significantly improved the design of the pick-up device for the pilot mining robot.

     

“Millipede” – an AFM data storage system at the frontier of nanotribology

The Millipede data storage concept is based on the parallel operation of a large number of micromechanical levers that function as AFM sensors. The technique holds promise to evolve into a novel ultrahigh-density, terabit-capacity, and high-data-rate storage technology. Thermomechanical writing and reading in very thin polymer (PMMA) films is used to store and sense 30–40 nm sized bits of similar pitch size, resulting in 400–500 Gbit/in² storage densities. High data rates are achieved by operating very large arrays (32×32) of AFM sensors in parallel. Batch-fabrication of 32×32 AFM cantilever array chips has been achieved, and array reading and writing have been demonstrated. An important consideration for the Millipede storage project is the polymer dynamics on the size scale of one bit. Scaling of rheological parameters measured for macroscopic polymer samples is likely to be incorrect due to the finite length of the underlying molecular polymer chain, a size that is comparable to the bit itself. In order to shed light on these issues we performed lifetime studies of regular arrays of nanometer size patterns using light-scattering techniques.     

Disturbance-rejection-based tuning of proportional–integral–derivative controllers by exploiting closed-loop plant data

A systematic data-based design method for tuning proportional–integral–derivative (PID) controllers for disturbance attenuation is proposed. In this method, a set of closed-loop plant data are directly exploited without using a process model. PID controller parameters for a control system that behaves as closely as possible to the reference model for disturbance rejection are derived. Two algorithms are developed to calculate the PID parameters. One algorithm determines the optimal time delay in the reference model by solving an optimization problem, whereas the other algorithm avoids the nonlinear optimization by using a simple approximation for the time delay term, enabling derivation of analytical PID tuning formulas. Because plant data integrals are used in the regression equations for calculating PID parameters, the two proposed algorithms are robust against measurement noises. Moreover, the controller tuning involves an adjustable design parameter that enables the user to achieve a trade-off between performance and robustness. Because of its closed-loop tuning capability, the proposed method can be applied online to improve (retune) existing underperforming controllers for stable, integrating, and unstable plants. Simulation examples covering a wide variety of process dynamics, including two examples related to reactor systems, are presented to demonstrate the effectiveness of the proposed tuning method.     

Preliminary tests of high-speed data communications protocol on the “Quasar” VLBI network

Results of preliminary experimental investigations with the aim of arranging high-speed data transmission in the electronic very long baseline interferometry (e-VLBI) mode are presented. The standard data transmission facilities and specialized Tsunami protocol are compared. The way of increasing the data transmission rate, based on the mechanism of decreasing the number of errors arising in the communication channel during data transmission, is recommended. It is concluded that the tested Tsunami protocol can be used as a base application of the data transmission in the real-time operation mode.     

Bayes filter for dynamic coordinate measurements – Accuracy improvment,data fusion and measurement uncertainty evaluation

This paper presents a novel methodology to improve the measurement accuracy of dynamic measurements. This is achieved by deducing an online Bayes optimal estimate of the true measurand given uncertain, noisy or incomplete measurements within the framework of sequential Monte Carlo methods. The estimation problem is formulated as a general Bayesian inference problem for nonlinear dynamic systems. The optimal estimate is represented by probability density functions, which enable an online, probabilistic data fusion as well as a Bayesian measurement uncertainty evaluation corresponding to the “Guide to the expression of uncertainty in measurement“. The efficiency and performance of the proposed methodology is verified and shown by dynamic coordinate measurements.     

Evaluation of a digital data acquisition system and optimization of n-γ discrimination for a compact neutron spectrometer

A compact NE213 liquid scintillation neutron spectrometer with a new digital data acquisition (DAQ) system is now in operation at the Physikalisch-Technische Bundesanstalt (PTB). With the DAQ system, developed by ENEA Frascati, neutron spectrometry with high count rates in the order of 5×10(5) s(-1) is possible, roughly an order of magnitude higher than with an analog acquisition system. To validate the DAQ system, a new data analysis code was developed and tests were done using measurements with 14-MeV neutrons made at the PTB accelerator. Additional analysis was carried out to optimize the two-gate method used for neutron and gamma (n-γ) discrimination. The best results were obtained with gates of 35 ns and 80 ns. This indicates that the fast and medium decay time components of the NE213 light emission are the ones that are relevant for n-γ discrimination with the digital acquisition system. This differs from what is normally implemented in the analog pulse shape discrimination modules, namely, the fast and long decay emissions of the scintillating light.     

Determining the singlet nn -scattering length from data on the n + d → p + n + n reaction yield by solving the inverse problem

The possibility of determining the nn-scattering length in the n + d → p + n + n reaction is considered. An inverse problem of reconstructing the dependence of the reaction yield on the energy of relative motion of two neutrons in the region of the nn final state interaction peak is solved. The proposed technique is tested using results of simulation of the nd breakup reaction. Original Russian Text ? S.V. Zuyev, E.S. Konobeevski, M.V. Mordovskoy, 2008, published in Pribory i Tekhnika Eksperimenta, 2008, No. 3, pp. 5–8.