Hideki Aoyama

A hybrid approach for fuzzy multi-attribute decision making in machine tool selection with consideration of the interactions of attributes

Global economic competition has spurred the manufacturing sector to improve and invest in modern equipment to satisfy the needs of the market. In particular, machine tool selection is the most important problem; it plays a primary role in the improvement of productivity and flexibility in the manufacturing environment and involves the imprecise, vague and uncertain information. This paper presents the hybrid approach of the fuzzy ANP (Analytic Network Process) and COPRAS-G (COmplex PRoportional ASsessment of alternatives with Grey relations) for fuzzy multi-attribute decision-making in evaluating machine tools with consideration of the interactions of the attributes. The fuzzy ANP is used to handle the imprecise, vague and uncertain information from expert judgments and model the interaction, feedback relationships and interdependence among the attributes to determine the weights of the attributes. COPRAS-G is employed to present the preference ratio of the alternatives in interval values with respect to each attribute and calculate the weighted priorities of the machine alternatives. Alternatives are ranked in ascending order by priority. As a demonstration of the proposed model, a numerical example is implemented based on the collected data and the literature. The result is then compared with the rankings provided by other methods such as TOPSIS-G, SAW-G and GRA. Moreover, a sensitivity analysis is conducted to verify the robustness of the ranking. The result highlights that the hybrid approach of the fuzzy ANP and COPRAS-G is a highly flexible tool and reaches an effective decision in machine tool selection.

PAS (Plasma activated sintering): Transient sintering process control for rapid consolidation of powders

Abstract A sintering method for the rapid consolidation of a variety of engineering materials in short time frames (seconds to minutes) is presented with a focus on the manufacturing potential of this novel Plasma Activated Sintering (PAS) process. PAS is a recent innovation pioneered by Sodick in Japan and is currently being used for the production of a number of engineering components, the manufacture of dense magnets by Matsushita Electric company being a prime example. The versatility of the PAS process allows very quick densification to near theoretical density in a number of metallic, ceramic, and multi-layer materials of interest in mechanical, electronic, and structural applications. In the present work we present the control mechanism of the PAS process including the experimental conditions, instrumentation, and process modeling aspects of this method. Our results on a wide variety of difficult-to-sinter materials are described along with micro structural characteristics. Finally, we project the future prospect of intelligent manufacturing systems based on the PAS technology and particularly outline the design of complex coupled motion controls for PAS systems.

A New Method for Detecting the Contact Point between a Touch Probe and a Surface

Abstract This paper deals with a newly developed touch probe which can directly detect the point between the surface of an object being measured and itself. The proposed method is based on the spherical potentiometer; that is, the probe ball is covered with a thin resistant film and four electrodes are symmetrically allocated on the upper part of the probe ball. By measuring the electric resistance between the four electrodes and the contact point, it is possible to determine where the point of contact is located on the probe ball. This paper describes the computer simulation for designing the probe, the development of the probe based on this principle, the system of measurement using the probe and a coordinate measuring machine, and an evaluation of the developed probe according to the results of experiments.

An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation

Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment.

Autonomous Process Planning with Real-Time Machining for Productive Sculptured Surface Manufacturing Based on Automatic Recognition of Geometric Features

Abstract The paper deals with a study on technologies to enhance the manufacturing productivity of a product consisting of sculptured surfaces. A process planning system coupled with real time machining is proposed such that the productive machining plan and tool motion can automatically be generated once available resources and machining know-how are given for the metal cutting-EDM mixed environment. The system proposed consists of geometry feature recognition, cutting mode and tool selection, real time tool path generation with adaptive feedrate generation using concurrent real time machining simulation. The system was prototyped to verify the feasibility. Successful results were obtained.

Development of a Magnetostrictive Torque Sensor for Milling Process Monitoring

This paper deals with a sensor system based on the magnetostrictive effect which is installed in a tool holder for sensing cutting torque in order to monitor the milling process. Changes in the magnetic permeability of ferromagnetic alloy layers formed onto a rotating shaft due to torque are detected by coils as changes in impedance without contacting the rotating shaft. By mounting the magnetostrictive sensor on a tool holder, it has become possible to detect cutting torque as close to the cutting point as possible. The accuracy of the proposed sensor system is confirmed through static and dynamic evaluation tests. In order to investigate the relationship between tool failure and cutting torque, cutting tests were performed. As the results, the possibility of estimating flank wear and tool fracture from cutting torque detected by the proposed sensor system is recognized.

Fiber optic surface topography measurement sensor and its design study

This paper presents some aspects of design approach, modeling, and experimental measurement results of a fiber optic-based surface topography measurement sensor that can measure surface roughness as well as the distance between the sensor tip and a surface and surface inclination angles. The working principle of the sensor is based on the detection of light intensity reflecting from the surface being measured. The sensor is very small and easy to operate. It can be attached to a coordinate measuring machine (CMM) to measure surface position coordinates, inclination angles, and surface roughness in a noncontact manner at one measurement setup. A theoretical model of intensity distribution and intensity detection has been established for the sensor. A three-factor and three-level experiment was designed to investigate the relationship between sensor performance and sensor design parameters. Two second-order regression models have been generated, which show that the central distance between the emitting and receiving fibers of a sensor has the strongest influence on the effective range of the sensor; whereas, the critical angle of a receiving fiber influences the sensitivity of the sensor most.

An Integrated MCDM Model for Conveyor Equipment Evaluation and Selection in an FMC Based on a Fuzzy AHP and Fuzzy ARAS in the Presence of Vagueness

The conveyor system plays a vital role in improving the performance of flexible manufacturing cells (FMCs). The conveyor selection problem involves the evaluation of a set of potential alternatives based on qualitative and quantitative criteria. This paper presents an integrated multi-criteria decision making (MCDM) model of a fuzzy AHP (analytic hierarchy process) and fuzzy ARAS (additive ratio assessment) for conveyor evaluation and selection. In this model, linguistic terms represented as triangular fuzzy numbers are used to quantify experts’ uncertain assessments of alternatives with respect to the criteria. The fuzzy set is then integrated into the AHP to determine the weights of the criteria. Finally, a fuzzy ARAS is used to calculate the weights of the alternatives. To demonstrate the effectiveness of the proposed model, a case study is performed of a practical example, and the results obtained demonstrate practical potential for the implementation of FMCs.

Optical Sensor for Detecting a Position and an Inclination

This paper deals with an optical sensor designed to automatically measure a sculptured surface geometry. The sensor can continuously and simultaneously detect a position vector (a gap distance) and a unit normal vector (an inclination angle) of a point to be measured without touching. In this paper, the principle of detecting a gap distance and an inclination angle is clarified, and the feasibility of the principle is tested by simulation and by a physical prototype. Developing a primitive prototype, the detectable range of a gap distance and surface inclination are evaluated by experiments. While performing the simulations and the experiments, it became clear that the sensor has a measured range of 20 mm for detecting a gap distance and a measured range from −70 to 70 degrees for detecting an inclination angle with regard to a diffuse surface.

Noncontact Probe for Continuous Measurement of Surface Inclination and Position Using Dynamic Irradiation of Light Beam

Summary The paper deals with a development of a new non-contact probe module for the high speed measurement of dimensions of a product. The probe module can continuously and simultaneously detect a position and a surface normal vector with custom signal processing algorithm developed. A probe module using multiple optical fibers was designed and a simulation was performed for verifying the proposed idea. A probe module was also prototyped and tested. A successful results were obtained and its performance coincided with the simulation. For practical application, a multi-beam dynamic irradiation probe using the developed module was designed and prototyped.