Hybrid intelligent control strategy. Supervising a DCS-controlled batch process

Considering the real employment situation of the disabled, it was concluded that there is demand for a robot system that can be used in a real manufacturing environment. To derive our mission statement, we conducted a survey with three criteria: `A. to assist the disabled as much as possible'; `B. to consider the real situation of employment for the disabled'; and `C. to provide assistance for the most necessary tasks for the disabled in the work space'. Based on the survey results, our goal can be stated as follows: To develop work assistive mobile robots to help persons with limb disabilities obtain jobs in manufacturing environments where they can perform simple manual labor. Here, simple labor includes such tasks as circuit inspection and moving boxes. For our goal, we developed two types of work assistive mobile robots, which are small enough to work in the confined environments of real factories. Work assistive mobile robot type I is equipped with a forklift to move boxes and a robotic arm to help with jobs requiring more dexterity. Robot type II is compact in size, adopting an omni-wheel driving mechanism, and is equipped with a lift having a foldable fork. We gathered feedback from empirical work done on the two robots.

Hybrid actuator–damper–bracing control (HDABC) system with intelligent strategy and soil–structure interaction

This paper proposes an interesting three-stage algorithm targeting at highly reliable high dimension composite system reliability evaluation using Importance Sampling (IS). The central idea is at the first stage (the Screening stage) picking out those bottle-neck components which have the most main impact on composite system reliability indexes calculation. The Screening process is specially customized for composite system to adaptively achieve the recognition process once the bottleneck percentage parameter μ is set reasonably. The relative perturbation value of each component is calculated firstly as the basis of recognition progress. In one time of iterations in recognition progress, a given percentage of the exciting bottle-neck components will be removed. After some iteration, those bottle-neck components will be screened out. The remaining Cross Entropy Optimization and Importance Sampling Evaluation stages are performed only considering the distortion of those bottle-neck components' sampling parameters. Numerical tests show that the method has good estimation accuracy performance and substantial variance reduction on highly reliable high dimension system. This also verifies the existence of degeneracy phenomenon of likelihood with the increase of dimension.

In Chapter 10, we presented the host environment for the case study. We now proceed to the application of the architecture, design tools and implementation models in a real manufacturing environment. The PAC development life cycle (outlined in Chapter 9), provides an excellent opportunity to experiment with possible PAC solutions. But, it may not adequately emphasize the difficulties of the transition from PAC simulation to full implementation in a manufacturing site. This migration path is paved with an array of site-specific technical and social parameters within the target environment, including the integration with existing applications (such as MRP and data collection systems), and the promotion of PAC, as a viable operational production control method, among those currently responsible for production operations.

From COTS Simulation Software to an Open-source Platform: A Use Case in the Medical Device Industry

Towards the improvement of tool condition monitoring systems in the manufacturing environment

In a real manufacturing environment, the set of tasks that should be scheduled is changing over the time, which means that scheduling problems are dynamic. Also, in order to adapt the manufacturing systems with fluctuations, such as machine failure and create bottleneck machines, various flexibilities are considered in this system. For the first time, in this research, we consider the operational flexibility and flexibility due to Parallel Machines (PM) with non-uniform speed in Dynamic Job Shop (DJS) and in the field of Flexible Dynamic Job-Shop with Parallel Machines (FDJSPM) model. After modeling the problem, an algorithm based on the principles of Genetic Algorithm (GA) with dynamic two-dimensional chromosomes is proposed. The results of proposed algorithm and comparison with meta-heuristic data in the literature indicate the improvement of solutions by 1.34 percent for different dimensions of the problem.

In this work two built-in database technologies were compared and applied to aggregation of data from a network of sensor equipped data collection nodes in a real manufacturing environment. The methods investigated are: data sharding and foreign data wrappers. The availability and feature set differences of the methods on some popular database management systems was compared and then a detailed case study on PostgreSQL DBMS was performed. For testing the concept in more realistic environment the sensor network was implemented using a number of Raspberry Pi computers with local relational database and with wireless connectivity to main aggregation database running on a much powerful server computer. Both database methods were applied on all nodes and the server and performance was measured for different types of aggregation queries. The very same data aggregation concepts presented here could be applied to any sensor network or to any Internet of things network.

Integrated process planning and scheduling is a significant research focus in recent years, which could improve the performance of manufacturing system. In real manufacturing environment, multi-objectives should be taken into consideration simultaneously during the machining process. Meanwhile, the processing time for each job is often imprecise in many real applications. Therefore, multi-objective integrated process planning and scheduling (IPPS) problem with fuzzy processing time is addressed in this paper. The processing time is described as triangular fuzzy number. A multi-objective genetic algorithm (MOGA) is designed to search for the Pareto solutions of multi-objective IPPS problem with fuzzy processing time. An instance has been designed to test the performance of proposed algorithm. The experiment result shows that the proposed MOGA could obtain satisfactory Pareto solutions for the multi-objective IPPS problem with fuzzy processing time.

After an integrated circuit (IC) design is complete, but before first silicon arrives from the manufacturing facility, the design team prepares a set of test patterns to isolate defective parts. Applying this test pattern set to every manufactured part reduces the fraction of defective parts erroneously sold to customers as defect-free parts. This fraction is referred to as the defect level (DL). However, many IC manufacturers quote defective part level, which is obtained by multiplying the defect level by one million to give the number of defective parts per million. Ideally, we could accurately estimate the defective part level by analyzing the circuit structure, the applied test-pattern set, and the manufacturing yield. If the expected defective part level exceeded some specified value, then either the test pattern set or (in extreme cases) the design could be modified to achieve adequate quality. Although the IC industry widely accepts stuck-at fault detection as a key test-quality figure of merit, it is nevertheless necessary to detect other defect types seen in real manufacturing environments. A defective-part-level model combined with a method for choosing test patterns that use site observation can predict defect levels in submicron ICs more accurately than simple stuck-at fault analysis.

While it is important to exhaustively verify IC designs for their functional performance, it is equally important to verify their robustness against spot defects, that is, to foresee what will happen to the design when it is exposed to defect conditions in a real manufacturing environment. One such verification is done by extracting the layout sites where defects can induce a functional failure of the design. Initial attempts to perform this verification task were based on a 'critical area extraction' of one layer at a time, neglecting the electrical significance of interrelationships between layers. A novel method to construct deterministically multilayer critical areas is presented. These critical areas are established on the theoretical basis of defect semantics and on the new concept of 'susceptible sites'. A system comprising several algorithms which in principle maintain simultaneously as many scan lines as the number of layers, in such a way that it is possible to keep track of the vertical and horizontal effects of defects, is developed. >

In a real manufacturing environment, different parts usually need to be processed using a single resource. Whenever a different part is introduced to a resource a new setup is needed, and this setup includes tool change costs. In most realistic problems the setup costs depend on the type of job just completed as well as on the job to be processed. In general, this problem can be likened to the “travelling salesman problem” that has been described in the literature. In this paper a new heuristic approach is introduced to be used whenever the cost of implementing an optimum seeking method is prohibitive. This method does not guarantee an optimum solution for all problems, but the importance lies in its ability to generate a very good solution, both rapidly and easily.

It is of interest to obtain the thermomechanical response of tools, equipment, and structural components in a real manufacturing environment. Microfabricated thin film thermocouples and strain gages are attractive for their small size and fast response. It is novel and challenging to fabricate these sensors on metal substrate and finally embed them into location of interest. Consequently, the materials (dielectric and metallic) constituting the sensor need to be characterized and optimized properly for reliability. We present here results of characterization and optimization of materials making a thermomechanical sensor to be embedded in metal structure.

There are lots of contact works with objects in works performed by manipulators. Into it, needs of the surface contact work of polish, grinding, application, paint, inspection, etc. are increasing increasingly in recent years. However, study to this was seldom done. For this background, in our study, in order to realize surface-surface contact work, the position/posture/force/moment hybrid control for 6-DOF manipulator was proposed, and hybrid control in the axis direction of constraint coordinates has been performed. In this paper, according of proposing a difference inverse kinematics method to return position errors and posture errors of constraint coordinates to angle errors of joint coordinates, the structure of the hybrid control with good control accuracy and practicality was built. Moreover, by proposing a posture component separation method, hybrid control was extended in the arbitrary direction from axes of constraint coordinates, and the surface-surface contact work of the arbitrary direction was realized. Furthermore, the character erasing experiment of a white board treated as an example of surface-surface contact work using a RPY type 6-DOF manipulator was performed, and it verified the effectiveness of our hybrid control to surface-surface contact work.

This paper proposes a new direct power control (DPC) of three-phase PWM rectifier based on intelligent techniques, in order to improve the dynamic performances of the conventional direct power control, where the conventional proportional integral (PI) controller is replaced by fuzzy logic controller (FLC) to adjust the dc bus voltage and the classical switching table is also replaced by a selector based on artificial neural networks (ANN) to generate the switching sequences of the PWM rectifier. This new control approach allows to maintain the dc bus voltage, the instantaneous active and reactive power to their reference values and also to minimize their ripples. The dynamic performances of this control technique were verified using Matlab/Simulink software under different conditions of simulation. The obtained results present better performance in terms of precision, robustness and reduction of harmonic disturbances.