logistic regression and response surface design for statistical modeling of investment casting process in metal foam production

Abstract A metal foam represents a promising material since it keeps the high mechanical properties of the metal while reducing the weight up to 90%. Among several manufacturing processes, the investment casting is a foundry process flexible enough to be suitable both for stochastic and for regular foams. This paper presents an experimental determination of the manufacturing process of metal regular foams by investment casting. The goal is to derive experimentally an actual formability map. The use of logistic regression and response surface design is proposed as an effective tool for determining a statistical model of the metal foam casting process

A Real-Time Condition Monitoring System by using Seasonal ARIMA Model and Control Charting

EnThis paper is concerned with research on early-failure monitoring systems for safety of railway systems. The work presented here have led to the development of ideas and techniques for the employment of time series modelling and control charting for on-line temperature monitoring of railcar brakes. A software package implementing the real-time monitoring scheme is presented. The temperature signal is sampled and the readings are filtered using a time-series model. In particular, a seasonal ARIMA model is exploited. The filtered signal, which has well defined statistical properties, is then plotted against proper control limits. The motivation of the research is the need for improved reliability of equipment and quality of service to metro passengers

A model-free approach for quality monitoring of Geometric Tolerances

Profile monitoring can be effectively adopted to detect unnatural behaviors of machining processes, i.e., to signal when the functional relationship used to model the geometric feature monitored changes with time. Most of the literature concerned with profile monitoring deals with the issue of model identification for the functional relationship of interest, as well as with control charting of the model parameters. In this chapter, a different approach is presented for profile monitoring, with a focus on quality monitoring of geometric tolerances. This approach does not require an analytical model for the statistical description of profiles considered, and it does not involve a control charting method. An algorithm which allows a computer to automatically learn from data the relationship to represent profiles in space is described. The proposed algorithm is usually referred to as a neural network and the data set, from which the relationship is learned, consists just of profiles representative of the process in its in-control state. Throughout this chapter, a test case related to roundness profiles obtained by turning and described in Chapter 11 is used as a reference. A verification study on the efficacy of the neural network shows that this approach may outperform the usual control charting method

An object oriented framework for manufacturing simulation.

Proceedings of the IX Workshop on Supervising and Diagnostics of Machining Systems, Special Symposium on Manufacturing simulation for industrial us

On-line statistical monitoring for mixing processes: An application in the dairy industry

The widespread application of electronic sensors and control systems makes industrial productions more efficient. In particular, several intelligent control systems, which mimic human analysis capabilities, are being used in the food-manufacturing industry. In this paper, a control system of a generic mixing process is presented. The proposed control system, which may be used in several food-manufacturing applications e.g. bread making as well as dairy production processes, has been exploited to monitor the level of both viscoelasticity and homogeneity of the mixing compound. The aim of the proposed control system is to optimise the mixing process by reducing the variability of the production quality level. The control system is based on measurements of the electrical power feeding the mixer motor. Thus, an additional benefit is that no sensor intrusion in the mixing machine is required. The proposed technique is exemplified by a real application in the dairy industry. The results have been compared with the operator's opinions indicating agreement with the proposed monitoring system. Copyright (C) 2003 IFAC

Process Performances Evaluation Using a Specific Shape Factor in the Case of Sheet Hydroforming

The increasing application of numerical simulation in metal forming field has helped engineers to solve problems one after another to manufacture a qualified formed product reducing the time required. Accurate simulation results are fundamental for the tooling and the product designs. Many factors can influence the final simulation result like for example a suitable yield criterion [1]. The wide application of numerical simulation is encouraging the development of highly accurate simulation procedures to meet industrial requirements. Currently, industrial goals of the forming simulation can be summarized in three main groups [2]: time reduction, costs reduction, increase of product quality. Many studies have been carried out about: materials, yield criteria [3, 4, 5] and plastic deformation [6, 7, 8], process parameters [9, 10, 11] and their optimization, geometry modification of the stamped part to evaluate if process responses modifications are required, reaching the goal to perform a virtual tryout of the whole deformation process [12]. In this paper proper metal forming numerical model and experimental analysis have been developed in order to foresee process responses in the case of sheet hydroforming technology. The interactions among the process performances and its variables are the most interesting aspects of the research because their knowledge means the possibility to drive the process feasibility which can be represented by the absence of ruptures and/or wrinkles in the stamped component. This paper analyzes the sheet thickness variation during the hydroforming process, according to a specifically defined “shape ratio”, useful to characterize product’s geometry. The latter is an hydroformed product characterized by a rectangular characteristic section with a drawing depth of 150mm, obtained by a hydroforming operation on a blank having a hexagonal shape. The physical and numerical experimentations were carried out on multiple geometries, different each others in punch radius and die radius, and on multiple materials, steel FeP04 (with a thickness of 1mm and 0,7mm) and Aluminum Al6061 (with a thickness of 0,7mm). The numerical simulation, validated by the experimental investigations [13,14], allowed to define a relationship, specific for sheet metal hydroforming, between the defined shape ratio and the key performance indicator, that is the percentage reduction thickness measured on specific areas of the formed part. The development of numerical models with an high level accuracy could give the real possibility to evaluate process feasibility with different combinations of geometrical and materials parameters without, at the first glance, simulation but only analyzing the specific curves (y = percentage reduction thickness, x = shape ratio