Open Architecture Modular Tool Kit for Motion and Machining Process Control

New demands are being placed on monitoring systems in the manufacturing environment because of recent developments in machining technology and machine tool design. In-process sensors are used to generate control signals to improve both the control and productivity of manufacturing systems. Numerous different sensors are available for monitoring and controlling the machining environment including force, power, and acoustic emission (AE) sensors. This paper first discusses the requirements for sensor technology for precision manufacturing process monitoring in general. Details are also given about AE and its application for process characterisation and monitoring in ultraprecision machining.

Research in automating the process level of machining operations has been conducted, in both academia and industry, over the past few decades. This work is motivated by a strong belief that research in this area will provide increased productivity, improved part quality, reduced costs, and relaxed machine design constraints. The basis for this belief is two-fold. First, machining process automation can be applied to both large batch production environments and small batch jobs. Second, process automation can autonomously tune machine parameters (feed, speed, depth of cut, etc.) on-line and off-line to substantially increase the machine tool’s performance in terms of part tolerances and surface finish, operation cycle time, etc. Process automation holds the promise of bridging the gap between product design and process planning, while reaching beyond the capability of a human operator. The success of manufacturing process automation hinges primarily on the effectiveness of the process monitoring and control systems. This paper discusses the evolution of machining process monitoring and control technologies and conducts an in-depth review of the state-of-the-art of these technologies over the past decade. The research in each area is highlighted with experimental and simulation examples. Open architecture software platforms that provide the means to implement process monitoring and control systems are also reviewed. The impact, industrial realization, and future trends of machining process monitoring and control technologies are also discussed.

Describes OFTT (OLE Fault Tolerance Technology), a fault tolerance middleware toolkit running on the Microsoft Windows NT operating system that provides the required fault tolerance for networked PCs in the context of industrial process monitoring and control applications. It is based on the Microsoft Component Object Model (COM) and consists of components that perform checkpoint-saving, failure detection, recovery and other fault tolerance functions. The ease with which this technology can be incorporated into an application represents the primary innovation. It is hoped that, by making fault tolerance more compatible with standard software architectures, more reliable PC-based monitoring and control systems can be built conveniently.

The acceleration of the spindle in the axial direction was measured when preharden steel was slotted with a square end mill under several cutting conditions. The signal of the accelerometer was stored and processed through digital Fourier transformation on a personal computer. The power spectra had peaks in a distinctive frequency range when chatter occurred. There is a threshold value of the ratio of the maximum intensity in the range to the one at the frequency of interrupted cutting by edges for detection of chatter.

The monitoring of machining process seems to be the crucial for effectiveness and accuracy. The precise monitoring needs fast, efficient, easy and open communication standard for data interchange or data acquisition. The use a popular, inexpensive and ordinary network system instead complicated and valuable professional/industrial field-bus is really attractive. The paper presents some conception of the office Ethernet implementation as data transmission structure for monitoring. The basic, laboratory tests with different protocols and configuration were done. As a conclusion several rules were formulated to help potential users.

Milling is one of the most important metal cutting processes. If we measure the cutting force, we can make cutting process optimum, prevent tool breakage, and improve efficiency of process. However in the case of using an end mill with small diameter, it is very difficult to identify whether cutting process is good or not. In this paper, we proposed the cutting force measurement technique by using image processing. In the technique, we captured a image of the end mill during cutting process, determined deflection of the tool and then estimated cutting force. Finally, we can estimate small cutting force with high accuracy.

Integrated monitoring system for discrete manufacturing processes is presented in the paper. The multilayer hardware and software reference model was developed. Original research are an answer for industry needs of the integration of information flow in production process. Reference model corresponds with proposed data model based on multilayer data tree allowing to describe orders, products, processes and save monitoring data. Elaborated models were implemented in the integrated monitoring system demonstrator developed in the project. It was built on the base of multiagent technology to assure high flexibility and openness on applying intelligent algorithms for data processing. Currently on the base of achieved experience an application integrated monitoring system for real production system is developed. In the article the main problems of monitoring integration are presented, including specificity of discrete production, data processing and future application of Cyber-Physical-Systems. Development of manufacturing systems is based more and more on taking an advantage of applying intelligent solutions into machine and production process control and monitoring. Connection of technical systems, machine tools and manufacturing processes monitoring with advanced information processing seems to be one of the most important areas of near future development. It will play important role in efficient operation and competitiveness of the whole production system. It is also important area of applying in the future Cyber-Physical-Systems that can radically improve functionally of monitoring systems and reduce the cost of its implementation.

ABSTRACTMachining process monitoring is essential to guarantee machining quality and reduce production cost, especially for the parts with complex structures and high accuracy requirement. However, effective machining process monitoring is still a challenge in industry. Particularly, a smooth communication between remote control computers and CNC (Computerized Numerical Control) systems is required. To address this requirement, a remote machining process monitoring method based on features and web is proposed. Machining feature model is established to facilitate the communication among the involved modules in the system. A web-based method is adopted to realize remote monitoring and control for multiple machines, as well as to alleviate the computational load of CNC systems. In addition, a feature-based database is constructed as a communication hub, where feature information, monitoring strategies and monitoring results are stored. A prototype system has been developed to validate the feasibility of the ...

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