scholarly journals Visualization of Control Processes a nd Code Validation

2021 ◽  
Vol 11 (1) ◽  
pp. 59-63
Author(s):  
Monika Rybczak ◽  
◽  
Dawid Trzcińśki ◽  
Natalia Wenta ◽  
◽  
...  
Keyword(s):  
Production Line ◽  
Control Process ◽  
Program Code ◽  
Programming Environments ◽  
Matlab Simulink ◽  
3D Object ◽  
Control Processes ◽  
Virtual Production ◽  
Code Validation ◽  
Process Visualization

The article contains an overview of articles related to the description of control process visualization. It provides short information on how to visualize the production line based on two programming environments: Factory IO and Inventor together with Matlab/Simulink. The analysis of these two environments concerns control of a virtual 3D object from a real PLC. Both virtual production line projects are based on control from the S7-1214 DC/DC/DC controller. Currently, there is a need to validate the program code or control process which has been done using several commercially available programs.

scholarly journals Synthesis of a Path-Planning Algorithm for Autonomous Robots Moving in a Game Environment during Collision Avoidance

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 675
Author(s):  
Józef Lisowski
Keyword(s):  
Mobile Robot ◽  
Autonomous Robots ◽  
Control Process ◽  
Matrix Game ◽  
Matlab Simulink ◽  
Planning Algorithm ◽  
Mobile Robot Control ◽  
Game Environment ◽  
Path Planning Algorithm ◽  
Made In

This paper describes and illustrates the optimization of a safe mobile robot control process in collision situations using the model of a multistep matrix game of many participants in the form of a dual linear programming problem. The synthesis of non-cooperative and cooperative game control software was performed in Matlab/Simulink software to determine the safe path of the robot when passing a greater number of other robots and obstacles. The operation of the game motion control algorithm of a mobile robot is illustrated by computer simulations made in the Matlab/Simulink program of two real previously recorded navigation situations while passing dozens of other autonomous mobile robots.

A Concept of a “Virtual Production Line” Produced by Integrating Databases and Models of Materials

MRS Bulletin ◽  
1993 ◽  
Vol 18 (7) ◽  
pp. 29-34 ◽  
Author(s):  
Shuichi Iwata
Keyword(s):  
Production Line ◽  
Ad Hoc ◽  
Intelligent System ◽  
Processing Parameters ◽  
Alloy Development ◽  
Bottom Up ◽  
Vast Number ◽  
Practical Applications ◽  
Virtual Production ◽  
Almost All

One of the requirements for an intelligent system is to construct a virtual reality in the computer. For materials development, the “reality” is a laboratory or a production line used to improve some aspect of a material by changing its composition, processing parameters, service conditions, etc. In the case of information in libraries, the reality is a search that uses a thesaurus and bibliographic (fact) databases. The greatest barrier faced by users of materials information is that of accessing necessary information through both a librarian's view and a scientific/technological expert's view. One of the objectives of a virtual production line is to reduce this barrier through user-friendly interfaces.In designing materials, two typical approaches are combined to solve a given problem. The first is a top-down approach, in which a number of requirements are resolved to a set of possible and practical solutions for satisfying these requirements to a certain level. Almost all alloy development has followed such an approach. The second approach is a bottom-up approach, where different materials properties are described on the basis of underlying theories, preferably using first principles and fundamental data. But the vast number of possible materials makes the bottom-up approach unrealistic on its own. Instead, semi-empirical approaches are needed to bridge the gap between ad hoc data sets for practical applications and results produced by the bottom-up approach using fundamental data and first-principle calculations.

scholarly journals The Control Process Effectiveness: Organization Versus Customer

2013 ◽  
Vol 11 (8) ◽  
pp. 345
Author(s):  
Ofer Barkai
Keyword(s):  
Quality Of Service ◽  
Customer Service ◽  
Internal Control ◽  
Service Providers ◽  
Control Process ◽  
Point Of View ◽  
Large Organization ◽  
Control Processes ◽  
Telecommunication Company

This research project, which was implemented in an organization whose primary function is providing service (Telecommunication company), studies the scope of the correlation between the quality of service from the customers point of view (customer survey) and the organization (Telecommunication company systems). The research is important both for economic and scientific reasons. It involves many organizational control units which require significant monetary investments. From a scientific point of view, the research is important because it can shed light on the asymmetrical point of view existing between customers and organizations. Organizations that are service providers place high importance on the quality of service and their image as perceived by their customers. Quality of service is measured through internal control processes and from there is passed on to the staff who are directly involved in customer service. In this study, we focus on a large organization which implements control processes and then provides service to customers. Therefore, the activities of this organization are judged first and foremost on the basis of the service quality provided. The existing internal control processes of the organization, which measure the standard of service provided on the basis of organizational benchmarks are separate from those that measure customer satisfaction. In this project, we analyze the correlation between the outlook of the customer and the results of internal control processes.

scholarly journals A NOTE ON COMONOTONICITY AND POSITIVITY OF THE CONTROL COMPONENTS OF DECOUPLED QUADRATIC FBSDE

2013 ◽  
Vol 13 (04) ◽  
pp. 1350005 ◽  
Author(s):  
GONÇALO DOS REIS ◽  
RICARDO J. N. DOS REIS
Keyword(s):  
Differential Equations ◽  
Stochastic Differential Equations ◽  
Control Process ◽  
Backward Stochastic Differential Equations ◽  
Quadratic Growth ◽  
Comparison Result ◽  
Control Processes

In this note we are concerned with the solution of Forward–Backward Stochastic Differential Equations (FBSDE) with drivers that grow quadratically in the control component (quadratic growth FBSDE or qgFBSDE). The main theorem is a comparison result that allows comparing componentwise the signs of the control processes of two different qgFBSDE. As a by-product one obtains conditions that allow establishing the positivity of the control process.

scholarly journals Anggaran Biaya Sebagai Alat Pengendalian Manajemen Pada PT Asuransi Jiwasraya (Persero) Bogor

2013 ◽  
Vol 1 (3) ◽  
pp. 193-202
Author(s):  
Dicky Alfian ◽  
Iriyadi Iriyadi ◽  
Udi Pramiudi
Keyword(s):  
Cost Control ◽  
Planning Process ◽  
Control Process ◽  
Management Control ◽  
Budget Planning ◽  
Control Processes ◽  
Good Management ◽  
Cost Planning ◽  
The Cost

One way to define the company's goals is to create a plan, one that cost planning is essential inthe operation of the company activity. Preparation, control, until the realization of the budget is animportant factor in the control of management. Good management control will be reflected from asound budget planning from start budgeting to realization in which the control of the use of thebudget includes the cost of the company. The purpose of this study was to determine the function ofa planning application to the realization anggarabn budget costs play an important role in themanagement control process in order to achieve the goals set previously by the company. Theresearch was conducted by the author. PT. Asuransi Jiwasraya (Persero) Bogor is located atPajajaran Street 45 Bogor. The results of this study show that the variance resulting from budgetplanning to the realization greatly affects the level of management control of the company. In otherwords, the efficiency of which is determined by the value of variance budget planning process aswell as cost control processes that will better demonstrate the value of the level of managementcontrol of the company.

scholarly journals Deep learning for the quality control of thermoforming food packages

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Núria Banús ◽  
Imma Boada ◽  
Pau Xiberta ◽  
Pol Toldrà ◽  
Narcís Bustins
Keyword(s):  
Computer Vision ◽  
Quality Control ◽  
Deep Learning ◽  
Production Line ◽  
Modular Design ◽  
Vision System ◽  
False Negative ◽  
Control Process ◽  
Food Packages ◽  
Quality Control Process

AbstractQuality control is a key process designed to ensure that only products satisfying the defined quality requirements reach the end consumer or the next step in a production line. In the food industry, in the packaging step, there are many products that are still evaluated by human operators. To automate the process and improve efficiency and effectiveness, computer vision and artificial intelligence techniques can be applied. This automation is challenging since specific strategies designed according to the application scenario are required. Focusing on the quality control of the sealing and closure of matrix-shaped thermoforming food packages, the aim of the article is to propose a deep-learning-based solution designed to automatically perform the quality control while satisfying production cadence and ensuring 100% inline inspection of the products. Particularly, the designed computer vision system and the image-based criteria defined to determine when a product has to be accepted or rejected are presented. In addition, the vision control software is described with special emphasis on the different convolutional neural network (CNN) architectures that have been considered (ResNet18, ResNet50, Vgg19 and DenseNet161, non-pre-trained and pre-trained on ImageNet) and on the specifically designed dataset. To test the solution, different experiments are carried out in the laboratory and also in a real scenario, concluding that the proposed CNN-based approach improves the efficiency and security of the quality control process. Optimal results are obtained with the pre-trained DenseNet161, achieving false positive rates that range from 0.03 to 0.30% and false negative rates that range from 0 to 0.07%, with a rejection rate between 0.64 and 5.09% of production, and being able to detect at least 99.93% of the sealing defects that occur in any production. The modular design of our solution as well as the provided description allow it to adapt to similar scenarios and to new deep-learning models to prevent the arrival of faulty products to end consumers by removing them from the automated production line.

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