Hsin-Te Liao

Analysis of Impact in Robotic Peg-in-Hole Assembly

This paper presents an approach for analyzing the dynamics of initial impact during robotic parts mating represented by peg-in-hole assembly. Lagranges impact model is used to derive a general form of impact equations for an industrial manipulator performing peg-in-hole assembly. Specific impact equations can then be generated for a given robot to analyze part motions and contact forces in the mating of parts. The impact equations of a SCARA robot are obtained and utilized to investigate how the system parameters affect force impulse and departure angle in the assembly of a peg with a chamfered hole. The resulting information is useful to robot manufacturers in design of robotic equipment and to robot users in determining optimal operational conditions. It is also useful for building an intelligent robot controller capable of deciding on proper values of operation parameters.

Optimization on selective laser sintering of metallic powder via design of experiments method

Purpose – The objective of this study is to investigate the effect of various parameters on rapid prototyping parts for processes of sintering metallic powder by using Nd:YAG laser via the design of experiments (DOE) method.Design/methodology/approach – Experiments based on the DOE method were utilized to determine an optimal parameter setting for achieving a minimum amount of porosities in specimens during the selective laser sintering (SLS) process. Analysis of variance (ANOVA) was further conducted to identify significant factors.Findings – A regression model predicting percentages of porosities under various conditions was developed when the traditional Taguchis approach failed to identify a feasible model due to strong interactions of controlled factors. The significant factors to the process were identified by ANOVA.Research limitations/implications – Four controlled factors including pulse frequencies and pulse durations of laser beams, times of strikes of a pulse applying on a single laser spot a...

A Study of Taguchi and Design of Experiments Method in Injection Molding Process for Polypropylene Components

This study analyzes contour distortions, wear mass losses and tensile properties of polypropylene (PP) composite components applied to the interior coffer of automobiles. The specimens are prepared under different injection molding conditions by changing melting temperatures, injection speeds, and injection pressures via three computer-controlled progressive strokes. The contour distortions, wear and tensile properties are selected as quality targets. The arrangement of sixteen experiments is based on an orthogonal array table. Both the Taguchi method and the design of experiments (DOE) method are applied to determine an optimal parameter setting. In addition, a side-by-side comparison of two different approaches is provided. In this study, regression models that link the controlled parameters and the targeted outputs are developed, and the mathematic models can be utilized to predict the contour distortions, wear and tensile properties at various injection molding conditions.

A PETRI NET BASED OFFLINE SIMULATION AND ONLINE DIAGNOSTIC PLATFORM FOR MANUFACTURING SYSTEMS

ABSTRACT To simulate and debug or diagnose manufacturing systems is always challenging. This paper presents a hybrid PLC-controlled and PC Visual Basic (VB)-based Human-Machine Interface (HMI) platform based on Petri net (PN) theory for Manufacturing Systems. An augmented PN model was adopted to design and simulate the operational sequence of the Flexible Manufacturing System (FMS) at the National Kaohsiung First University of Science and Technology (NKFUST). With the simulated PN model, the control sequences were quickly translated into PLC programs. A PC-based HMI monitoring system based on the PN model was developed to provide an intuitive offline simulation and online diagnostic tools for the FMS. This hybrid system shows many of advantages by using the economical discrete control unit with PLC, and PC-based HMI using PN model as a base. The discrete event control sequence of an FMS can be easily modeled and evaluated before its build-up. More importantly, it can be diagnosed online when the system is malfunctioning. That is, the presented system provides an adequate means for offline system design, simulation, performance evaluation, and quick online system diagnostic.

Parts Mating Aided by Constant-Amplitude Sinusoidal Motions

This paper presents an analytical and experimental investigation of engagement of parts aided by two orthogonal constant-amplitude sinusoidal motions in mechanical assembly. In the analytical investigation we analyze how the amplitudes, frequencies, frequency ratio, and phase angle of the two motions affect the engagement. A numerical technique is developed for selecting these parameters, and a parts engagement strategy capable of recognizing various failure situations in peg-in-hole assembly is developed. Experiments are conducted to verify the validity of the parts engagement strategy as well as to provide useful information about the characteristics of contact force during the engagement.

Using a d-optimal mixture design to study the thermal properties of short glass fiber- and polytetrafluoroethylene-reinforced polycarbonate composites

This study analyzed variations of thermal properties that depend on the injection molding techniques during the blending of short glass fiber (SGF)- and polytetrafluoroethylene (PTFE)-reinforced polycarbonate (PC) composites. The proposed planning of blending experiments is using a d-optimal mixture design (DMD). The thermal conductivity and thermal expansion coefficient were selected for discussion. Nine experimental runs, based on a DMD method, utilized to train the back-propagation neural network (BPNN), and then the simulated annealing algorithm (SAA) approach is applied to search for an optimal mixture ratio setting. In addition, the result of BPNN integrating SAA was also compared with response surface methodology (RSM) approach. The results of confirmation experiment show that DMD, RSM, and BPNN integrating SAA method are effective tools for the optimization of reinforced process. Furthermore, analysis of variance and response surface graphs were applied to identify the effect of mixture ratio of SGF- and PTFE-reinforced PC composites for the thermal conductivity and thermal expansion coefficient.

Development of A Petri Net-Based Reengineering Simulation System: A Case Study

Researchers always intend to pursue the convenient and integrated tools for restoring the complexity of industrial automated systems. In this paper, a PC-based with PC visual basic-based (VB-Based) human-machine interface (HMI) is developed by using Petri nets (PN) technique for the simulation of an industrial automated system. The result brings many advantages to the reality of the automated control world. It not only reduces the restore time of the automated systems, prevents the cost of equipment malfunction, but also builds the panel of the humanity for the system. The developed sequence table has proved as an important role of control process for a discrete-event control system (DECS). This paper also discusses a systematic method to convert the sequence table to Petri nets so the barriers of the conversion technique can be easily reduced.

Optimization on Selective Fiber Laser Sintering of Tri-Metallic Powders via Design of Experiments Method

The objective of this research is to investigate the effect of various parameters on rapid prototyping parts during the process of sintering metal powder by using fiber laser. In order to minimize the percentage of porosities of rapid prototyping (RP) products, sintering a mixture of three metallic powders are investigated. Three metallic powders which are used in this research are Cooper, Iron and Nickel (particle size of Cooper is 5μm, Iron is 70μm and Nickel is 70μm). In addition, control factors and their alternate levels-two levels with 48 run experiments will be identified. The Design of Experiment (DOE) and Analysis of Variance (ANOVA) are used to analyze the results of modeling process. After the ANOVA, a regression model predicting percentages of porosities under various conditions was developed when the traditional Taguchis approach failed to identify a feasible model due to strong interactions of controlled factors.

Optimization on Selective Fiber Laser Sintering of Metallic Powder

Purpose – The objective of this study is to investigate the effect of various parameters on rapid prototyping parts for processes of sintering metallic powder by using fiber laser via the design of experiments (DOE) method. Design/methodology/approach – Experiments based on the DOE method were utilized to determine an optimal parameter setting for achieving a minimum amount of porosities in specimens during the selective laser sintering (SLS) process. Analysis of variance (ANOVA) was further conducted to identify significant factors. Findings – A regression model predicting percentages of porosities under various conditions was developed when the traditional Taguchi’s approach failed to identify a feasible model due to strong interactions of controlled factors. The significant factors to the process were identified by ANOVA. Research limitations/implications – Four controlled factors including pulse frequencies and scan rate of laser beams, laser power and scan line spacing with particle sizes of 5µm of the powder base material had significant influence on the sintering process. Future investigation planned to be carried out for achieving multiple quality targets such as the hardness and the density for 3D parts. Originality/value – The implementation of the DOE method provided a systematic approach to identify an optimal parameter setting of the SLS process; thus, the efficiency of designing optimal parameters was greatly improved. This approach could be easily extended to 3D cases by just including additional parameters into the design. Additionally, utilization of the normality analysis on the residual data ensured that the selected model was adequate and extracted all applicable information from the experimental data.

Development of an Intelligent Grey-RSS Navigation System for Mobile Robots

This study aims at developing an intelligent navigation system for mobile robots to eliminate the cumulative errors caused by using a conventional optical encoder. The optical encoder for mobile robots is supplanted by an intelligent Grey-RSS navigation system (IGRNS) with a RFID system embedded with a RSS (Received Signal Strength) location estimator and a Grey predictor for robot rotation angle prediction. The RFID system identifies the target with active RFID tag. The RSS location estimator then calculates the possible route of robot. The Grey controller optimizes the traveling route quickly. The simulation results show that the proposed IGRNS can reduce robot’s unstable rotation when locating the target. With IGRNS, the mobile robot takes fewer steps to reach target quickly. The performance of IGRNS is better than the one with the RSS navigation system alone.© 2012 ASME