A framework for machining optimisation based on STEP-NC

Inappropriate machining conditions such as cutting forces cause tool failures, poor surface quality and worst of all machine breakdowns. This may be avoided by using optimal machining parameters, e.g. feed-rate, and continuing to monitor it throughout the machining process. To optimize feed-rate, we propose a system that consists of an optimisation module, a process control module and a knowledge based evaluation module. STEP-NC is the underlying data model for optimisation. Given the nominal powers, the cutting force can be estimated based on the higher-level production information such as workpiece properties, tool materials and geometries, and machine capabilities. The main function of the Process Control module is process monitoring and control. The output is the desired actual feed-rate. Finally, the actual feed-rate is recorded and evaluated in the Knowledge Based Evaluation module.     

An expert system for setting parameters in machining processes

In this paper, an hybrid system is proposed for setting machining parameters from experimental data. A symbolic regression alpha–beta is used to build mathematical models. Every model is validated using statistical analysis then evolutionary computation is used to minimize or maximize the generated model. Symbolic regression α–β is used to build mathematical models by estimation of distribution algorithms. A practical case considering measured data of two machining process on three materials are used to illustrate the utility of the expert system because generates a set of parameters that improve the machining process.     

STEP-NC enabled on-line inspection in support of closed-loop machining

 The object-oriented STEP-NC data model provides a seamless and integrated programming interface for on-machine (or also known as on-line or in-line) inspections as well as interoperable manufacturing. This paper proposes a STEP-NC data model for on-line inspections. A framework of STEP-NC enabled closed-loop machining is also presented. The aim is to achieve a fully closed computer-aided design, process planning, machining and inspection chain. A new version of STEP-NC Interpreter has been developed to implement the proposed framework. A case study is included to demonstrate the implementation.     

An intelligent supervision system for open loop controlled processes

On-line manufacturing systems for continuous production are traditionally checked by constant time-based inspection and statistical process control processes. In the monitoring operation of large scale process plants, it is important to detect and locate process variables as they can significantly modify the operation and quality of the products involved. The present paper explores an alternative for monitoring these systems that uses the open loop control paradigm. The proposed method is defined and presented as an application for one particular industrial process—rubber die extrusion. The advantages of this method for this particular application, including its implementation throughout a multi-agent system, compatible with the HoloMAS paradigm for managing, modeling and supporting complex systems, are also discussed.     

An integrated fixture planning and analysis system for machining processes

Fixture planning is an important part of computer-aided process planning (CAPP), which is the link between design and manufacturing in a CIM environment. This paper presents a rational approach to computer-assisted fixture planning (CAFP), emphasizing integration of fixture planning with process planning, an issue that has not been adequately addressed until very recently. A systematic approach to fixture selection is outlined for planning of modular fixtures. A prototype CAPP-CAFP system has been developed at UCLA and linked to a commercial CAD system, namely, CADAM. Part design information can be extracted from the CAD model and multiple-view engineering drawings of a part stored in the CADAM system. Modular fixture elements can be selected automatically by the CAPP-CAFP system and the generated fixture layout can be displayed on the screen. Included also in the system is a fixture analysis module for verification and rationalization of a fixturing scheme. The force analysis module has a built-in local optimization routine that can determine the clamping forces of more reasonable magnitudes. The friction forces between the fixture and the workpiece can also be considered for simple cases.     

AUTO_SAFE: An expert controller for sequential and batch sequential processes

It is generally recognised that industrial processes depend heavily on sequential control. Paradoxically, this technique of control has received from control theorists, less attention than it deserves. In view of its logical basis, this class of control is an ideal candidate for rule-based expert systems. Features of one such expert system are presented in this paper, along with observations related to the development of expert systems for process control.     

An intelligent approach for the prediction of surface roughness in ball-end machining of polypropylene

Manufacturing paradigms over the last 150 years have changed from craft production, to mass production and now to mass customisation. One further extension of mass customisation is personalised manufacture, which is the concept of providing bespoke products to the individual consumer. As a result this has brought about the need for a greater degree of sophistication in manufacturing practises and the technologies employed. This bespoke form of manufacture of consumer goods is now being pursued on CNC machining centres as opposed to the alternative of highly expensive rapid prototyping methods. The problem with this form of manufacture is that the products are generally free formed objects which require sophisticated setups and machining. Ball-end machining is a method used to create cusp-type geometry, which is employed on CNC machines to create sculptured surfaces. The objective of this research is to provide a predictive model using a design of experiments strategy to obtain optimised machining parameters for a specific surface roughness in ball-end machining of polypropylene. This paper reports on new manufacturing knowledge to machine polypropylene using ball-end tooling in order to generate personalised sculptured surface products.     

Constrained SPSA controller for operations processes

Continuous quality improvement calls for employing methodologies that assist in continual reduction of variations in process performance characteristics around their target values. The study considers a case in which some of the operations process parameters/inputs are required to take values in pre-specified ranges. To improve the process performance while accounting for these requirements, the study employs a neural network-based model-free controller along with the penalty function. Simultaneous perturbation stochastic gradient approximation method is used to iteratively estimate the weights of neural network and as a result to estimate the control values. Furthermore, the study uses a special cause control chart to monitor the performance of the controller in reducing the process variations and to signal the change in the process dynamics. Simulation findings indicate that the neural network model-free provides control values that result in fewer nonconforming outputs than when the requirements are not incorporated in optimization process     

A generic controller architecture for intelligent robotic systems

This paper describes a research program to develop a novel reference architecture and design philosophy for an advanced robot controller for a new generation of robots. It is suggested that a new approach to robot controller design is required in order to bring the present generation of industrial robots in line with current and foreseeable technological developments. The paper also describes a prototype controller that has been developed using this design philosophy, and its deployment on an experimental robot. Practical results are presented from a series of investigations undertaken to illustrate the performance of the controller.     

基于PIC单片机的太阳能路灯智能控制器

针对太阳能控制系统的特点,探讨了太阳能路灯控制系统各部件的选用,设计了一种基于PIC16F877单片机的智能控制器.提出了可行的太阳能电池最大功率点跟踪方法和合理的蓄电池充放电策略.该控制器具有电路结构简单、可靠性高、实用性强等特点.     

An advanced refresh graphics controller with some novel features

The development of a more cost effective graphics controller, aiming at less analogue circuitary with fewer adjustments and an easier method to change drawing speed.     

眼睛理疗仪智能控制器设计

眼睛理疗仪智能控制器主要由主控制中心、人机交互系统（包括形状触摸控制、触屏控制、语音控制）、电机驱动模块、红外理疗模块、电磁理疗模块、音乐模块组成。主控中心通过压力传感器、温度传感器、加速度传感器实时监测各项参数。理疗仪具有多种理疗方式：振动按摩、穴位定点按摩、硅胶体滑动按摩、红外理疗、电磁理疗,以及上述方式的任意组合。通过合理的软件算法,实现控制方式的智能化、人性化,实现理疗效果的最佳化。     

Optimal controller tuning for nonlinear processes

The present work proposes a systematic methodology for the optimal selection of controller parameters in the sense of minimizing a performance index, which is a quadratic function of the tracking error and the control effort. The performance index is calculated explicitly as an algebraic function of the controller parameters by solving Zubov's partial differential equation (PDE). Standard optimization techniques are then employed for the calculation of the optimal values of the controller parameters. The solution of Zubov's PDE is also used to estimate the closed-loop stability region for the chosen values of the controller parameters. The proposed approach is finally illustrated in a chemical reactor control problem.     

Parameter optimization of advanced machining processes using cuckoo optimization algorithm and hoopoe heuristic

Unconventional machining processes (communally named advanced or modern machining processes) are widely used by manufacturing industries. These advanced machining processes allow producing complex profiles and high quality-products. However, several process parameters should be optimized to achieve this end. In this paper, the optimization of process parameters of two conventional and four advanced machining processes is investigated: drilling process, grinding process, abrasive jet machining, abrasive water jet machining, ultrasonic machining, and water jet machining, respectively. This research employed two bio-inspired algorithms called the cuckoo optimization algorithm and the hoopoe heuristic to optimize the machining control parameters of these processes. The obtained results are compared with other optimization algorithms described and applied in the literature.     

An integrated intelligent machining system for axisymmetric parts using PC-based CAD and CAM software packages

Machining process planning involves the formation of a set of directions describing the machining operations required to transform raw stock into a finished part. Conventional process planning, performed manually, relies on the knowledge and competence of an experienced process planner and tends to be time consuming and error prone. In the past two decades, much effort has been spent on improving process planning by utilizing the power of a computer to emulate the capabilities of an experienced planner. During the same period, computer-aided design (CAD) and computer-aided manufacturing (CAM) software has been developed to enhance design productivity and to assist the NC code generation facets of the machining process. The entire planning process may be automated be integrating CAD and CAM using computer-aided process planing (CAPP). The research described in this paper outlines the design and development of an intelligent CAPP system integrating two commercial CAD and CAM software packages, Autocad and Mastercam.     

Computer aided setup planning for machining processes

This paper deals with an automatic setup planning system for machining processes of prismatic parts. The proposed system concurrently implements both machining sequences of reference surfaces and machining sequences of features for the purpose of minimizing number of setups in setup planning. Experienced planners' knowledge are represented as rules and used for machining sequences of reference surfaces and they are implemented by using EXSYS. A case study is performed to evaluate the performance of the proposed system.     

Integration framework for intelligent manufacturing processes

In this article, we describe a new approach to applying distributed artificial intelligence techniques to manufacturing processes. The construction of intelligent systems is one of the most important techniques among artificial intelligence research. Our goal is to develop an integrated intelligent system for real time manufacturing processes. An integrated intelligent system is a large knowledge integration environment that consists of several symbolic reasoning systems (expert systems) and numerical computation packages. These software programs are controlled by a meta-system which manages the selection, operation and communication of these programs. A meta-system can be implemented in different language environments and applied to many disciplines. This new architecture can serve as a universal configuration to develop high performance intelligent systems for many complicated industrial applications in real world domains.To whom all correspondence should be addressed.     

An intelligent scheduling system using fuzzy logic controller for management of services in WiMAX networks

The appearance of media applications with high bandwidth and quality of service requirements has made a significant impact in telecommunications technology. In this direction, the IEEE802.16 has defined wireless access systems called WiMAX. These systems provide high-speed communications over a long distance. For this purpose some service classes with QoS requirements are defined; but the QoS scheduler is not standardized in IEEE802.16. The scheduling mechanism has a significant effect on the performance of WiMAX systems for use of bandwidth and radio resources. Some scheduling algorithms have been introduced by researchers; but they only provide some limited aspects of QoS. An intelligent decision support system is therefore necessary for scheduling. In this paper a fuzzy based scheduling system is proposed for compounds of real-time and non-real-time polling services which provide QoS requirements and fairness in dynamic conditions. A series of simulation experiments have been carried out to evaluate the performance of the proposed scheduling algorithm in terms of latency and throughput QoS parameters. The results show that the proposed method performs effectively regarding both of these criteria and achieves proportional system performance and fairness among different types of traffic.