Diagnostics of Errors at Component Surface by Vision Recognition in Production Systems

2014 ◽  
Vol 616 ◽  
pp. 227-235 ◽  
Author(s):  
Kamil Židek ◽  
Vladislav Maxim ◽  
Radoslav Sadecký
Keyword(s):  
Production Line ◽  
Surface Coverage ◽  
Production Systems ◽  
Conveyor Belt ◽  
Camera System ◽  
C Language ◽  
Edge Detectors ◽  
Part Surface ◽  
Imperfect Coverage ◽  
Scratch Detection

The article deals with the diagnostics of components surface after painting by camera system in real-time. This solution is especially suitable for implementation to automatized production line above the conveyor belt. The faults on the part surface can be detected as scratches, imperfect surface coverage and dirt stuck to the surface. The scratch detection is based on edge detectors, imperfect coverage are checked by histogram comparison and all other errors are detected by counter detectors. The developed software uses open source library OpenCV and is written in C++ language. The software solution is platform independent. Final algorithm is implemented to embedded device based on SoC.

PERFORMANCE EVALUATION OF GENETIC DISTRIBUTED FUZZY CONTROLLERS FOR MULTI-PART-TYPE PRODUCTION LINE

2007 ◽  
Vol 06 (02) ◽  
pp. 115-128
Author(s):  
SEYED MAHDI HOMAYOUNI ◽  
TANG SAI HONG ◽  
NAPSIAH ISMAIL
Keyword(s):  
Genetic Algorithm ◽  
Performance Evaluation ◽  
Objective Function ◽  
Production Rate ◽  
Production Line ◽  
Production Systems ◽  
Membership Functions ◽  
Part Type ◽  
High Penalty ◽  
Single Part

Genetic distributed fuzzy (GDF) controllers are proposed for multi-part-type production line. These production systems can produce more than one part type. For these systems, "production rate" and "priority of production" for each part type is determined by production controllers. The GDF controllers have already been applied to single-part-type production systems. The methodology is illustrated and evaluated using a two-part-type production line. For these controllers, genetic algorithm (GA) is used to tune the membership functions (MFs) of GDF. The objective function of the GDF controllers minimizes the surplus level in production line. The results show that GDF controllers can improve the performance of production systems. GDF controllers show their abilities in reducing the backlog level. In production systems in which the backlog has a high penalty or is not allowed, the implementation of GDF controllers is advisable.

Identification of Randomly Distributed Objects

2015 ◽  
Vol 791 ◽  
pp. 184-188
Author(s):  
Rudolf Jánoš ◽  
Jozef Varga
Keyword(s):  
Conveyor Belt ◽  
Distributed Objects ◽  
Camera System ◽  
Position And Orientation

This article describes the possibilities of identifying a randomly distributed objects due to the removal of parts from the conveyor belt, which is part of the workplace for assembly of the components. A specific feature of this work is that the installation is carried out with the robot SCARA, which take parts from the conveyor. Parts on the conveyor are unoriented, therefore it is necessary to use a camera system to detect the position and orientation of parts. Because of this, it is necessary to carry out the control lines across the moving conveyor. Recognition, identification, location and orientation of the proposed method is sufficiently robust and easily adaptable to the different type of components.

Standalone Throughput Analysis on the Wave Propagation of Disturbances in Production Sub-Systems

2013 ◽  
Vol 135 (5) ◽  
Author(s):  
Yang Li ◽  
Qing Chang ◽  
Michael P. Brundage ◽  
Guoxian Xiao ◽  
Stephan Biller
Keyword(s):  
Line Segment ◽  
Production Line ◽  
Evaluation Method ◽  
Production Systems ◽  
System Productivity ◽  
Serial Production ◽  
Multistage Manufacturing ◽  
Performance Indexes ◽  
Single Station ◽  
Definition Of

Standalone throughput (SAT) of a single station is one of the most widely used performance indexes in industry due to its clear definition, ease of evaluation and the ability to provide a guidance for continuous improvement in production systems. A complex multistage manufacturing system is typically segmented into several subsystems for efficient local management. It is important to evaluate performance of each subsystem to improve overall system productivity. However, the definition of standalone throughput of a production subsystem is not as clear as for a single station in current literatures or in practice, not to say an effective evaluation method. This paper deals with the standalone throughput of a serial production line segment. The definition and implication of standalone throughput of a line segment is discussed. A data driven method is developed based on online production data and is proved analytically under a practical assumption. In addition, the method is verified through simulation case studies to be an accurate and fast estimation of the standalone throughput of a production line segment.

scholarly journals Application of Failure Mode Effect and Criticality Analysis (FMECA) to a Computer Integrated Manufacturing (CIM) Conveyor Belt

2018 ◽  
Vol 8 (3) ◽  
pp. 3023-3027
Author(s):  
I. Elbadawi ◽  
M. A. Ashmawy ◽  
W. A. Yusmawiza ◽  
I. A. Chaudhry ◽  
N. B. Ali ◽  
...  
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Production Systems ◽  
Conveyor Belt ◽  
Computer Integrated Manufacturing ◽  
Formal Specifications ◽  
Production Time ◽  
Integrated Manufacturing ◽  
Mode Effect ◽  
Criticality Analysis

Fault finding and failure predicting techniques in manufacturing and production systems often involve forecasting failures, their effects, and occurrences. The majority of these techniques predict failures that may appear during the regular system production time. However, they do not estimate the failure modes and they require extensive source code instrumentation. In this study, we suggest an approach for predicting failure occurrences and modes during system production time intervals at the University of Hail (UoH). The aim of this project is to implement failure mode effect and criticality analysis (FMECA) on computer integrated manufacturing (CIM) conveyors to determine the effect of various failures on the CIM conveyor belt by ranking and prioritizing each failure according to its risk priority number (RPN). We incorporated the results of FMECA in the development of formal specifications of fail-safe CIM conveyor belt systems. The results show that the highest RPN values are for motor over current failure (450), conveyor chase of vibration (400), belt run off at the head pulley (200), accumulated dirt (180), and Bowed belt (150). The study concludes that performing FMECA is highly effective in improving CIM conveyor belt reliability and safety in the mechanical engineering workshop at UoH.

scholarly journals Utilization of computer simulation for optimization of furniture production system

BioResources ◽  
2020 ◽  
Vol 15 (3) ◽  
pp. 6752-6765
Author(s):  
Roman Bambura ◽  
Erika Sujová ◽  
Helena Čierna
Keyword(s):  
Computer Simulation ◽  
Production System ◽  
Production Line ◽  
Production Systems ◽  
Discrete Event ◽  
Simulation Software ◽  
Production Optimization ◽  
Furniture Manufacturing ◽  
Production Processes ◽  
Method Of Production

Computer simulation methods are currently used to simulate production processes and optimize production systems. Computer simulation is one of the most effective tools for implementation of Industry 4.0 principles in industrial practice. This research focused on the optimization of production processes in furniture production using simulation, which is an innovative method of production optimization for furniture manufacturers. The aim of this research was to improve the production system of Slovak furniture manufacturing enterprise by creating a discrete event simulation model of production based on the analysis of its current state. Improvement indicators are specific parameters of the production system, which primarily include material flow, productivity, and workload utilization. First, with the use of Tecnomatix Plant Simulation software and the collected real production data, the original production system processes were simulated and analyzed. Second, the incorporation of more powerful devices was proposed to improve the production line. Third, the proposed improvements were simulated and analyzed. The result of this research was a statistical comparison of the parameters of the current production line and the proposed production improvements.

scholarly journals Influence of Different Production Systems on the Quality and Shelf Life of Poultry Meat: A Case Study in the German Sector

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Antonia Albrecht ◽  
Martin Hebel ◽  
Maureen Mittler ◽  
Carola Hurck ◽  
Katharina Kustwan ◽  
...  
Keyword(s):  
Lipid Oxidation ◽  
Shelf Life ◽  
Meat Quality ◽  
Production Line ◽  
Production Systems ◽  
Quality Parameters ◽  
Poultry Meat ◽  
Poultry Production ◽  
Conventional Production ◽  
White Striping

Production-specific factors, such as breeding, diet, and stress, are known to influence meat quality, but the effect of different husbandry systems on the development of quality parameters and shelf life has hardly been investigated. Thus, the aim of the study was the investigation of an alternative production system based on a slow-growing, corn-fed, and antibiotics-free chicken line compared with conventional poultry production. Additionally, the effect on meat quality, microbiology, and spoilage was analyzed. In total, 221 breast filets from a German poultry meat producer were investigated. Nutritional, biochemical, and cooking loss analyses were conducted on a subset of samples 24 h after storage. The rest of the samples were stored aerobically at 4°C, and the spoilage process was characterized by investigating pH, color, lipid oxidation, microbiology, and sensory attributes subsequently every two days during storage. The alternative production line showed a significantly healthier nutritional profile with a higher protein and lower fat content. Additionally, the amount of L-lactic acid and D-glucose was significantly higher than in the conventional production line. The color values differed between both production lines, with the corn-fed line displaying more yellowish filets. The lipid oxidation and microbial spoilage were not affected by the production line. The shelf life did not differ between the investigation groups and was deemed 7 days in both cases. Despite the highest severity of white striping being observed most in the conventional production line, there was no overall difference in the incidence among groups. The purchase decision was affected by the occurrence of white striping and showed a tendency for a higher acceptance for the alternative production line.

Design Alternatives of Intelligent Camera System for Check Parts at the Intelligent Manufacturing-Assembly Cell

2011 ◽  
Vol 58-60 ◽  
pp. 2262-2266 ◽  
Author(s):  
Nina Danišová ◽  
Roman Ruzarovsky ◽  
Karol Velíšek
Keyword(s):  
Intelligent Systems ◽  
Production Systems ◽  
Intelligent Manufacturing ◽  
Camera System ◽  
Industrial Companies ◽  
Camera Systems ◽  
Assembly Cell ◽  
Design Alternatives ◽  
Manufacturing Assembly ◽  
New Generation

In this contribution are presented designs of intelligent camera systems at the intelligent manufacturing-assembly cell. Intelligent manufacturing-assembly cell is situated at the Institute of production systems and applied mechanics. For this intelligent cell was designed intelligent camera system with industrial camera. All design alternatives of check station with camera system go out knowledge of intelligent systems. Intelligent systems as systems of new generation are loading gradually at mechanical production, when they remove person from production process and they shorten production times. Intelligent systems are situated to day at all production processes of large industrial companies.

scholarly journals Application of OEE for productivity analysis: a case study of a production line from the pulp and paper industry

DYNA ◽  
2019 ◽  
Vol 86 (211) ◽  
pp. 9-16 ◽  
Author(s):  
Jairo J .O Andrade ◽  
Daniel Dreher Silveira
Keyword(s):  
Continuous Improvement ◽  
Production Line ◽  
Production Systems ◽  
Paper Industry ◽  
Pulp And Paper Industry ◽  
Pulp And Paper ◽  
Production Costs ◽  
Productivity Analysis ◽  
Quality Performance

The overall equipment effectiveness (OEE) is an indicator used in the management and continuous improvement of production systems, and is useful in identifying losses, thus reducing production costs. By analyzing the results of this indicator, the operation manager must make decisions to eliminate or reduce losses in the process. This study investigated the application of the OEE indicator in one production line in the pulp and paper industry. The implementation of OEE was performed in stages with a detailed analysis of the indicators that compose the OEE (quality, performance, and availability) to identify possible improvements. Thus, actions were implemented to improve the OEE quality index. This study provided important information that enabled the operation manager to diagnose and minimize the occurrence of failures and losses, which is often hidden and unknown to those involved in the production system.

Overall equipment effectiveness (OEE) evaluation for an automated ice cream production line

2019 ◽  
Vol 69 (5) ◽  
pp. 1009-1032 ◽  
Author(s):  
Panagiotis H. Tsarouhas
Keyword(s):  
Operations Management ◽  
Production System ◽  
Production Line ◽  
Production Systems ◽  
Ice Cream ◽  
Management Tools ◽  
Content Type ◽  
Pareto Analysis ◽  
Automated Production ◽  
Working Day

Purpose As overall equipment effectiveness (OEE) is a metric to estimate equipment effectiveness of production systems, the purpose of this paper is to identify strategic management tools and techniques based on OEE assessment of the ice cream production line. Design/methodology/approach This paper presents the collection and the analysis of data for ice cream production under real working conditions. The data cover a period of eight months. A framework process to improve the OEE of an automated production system was proposed. Six major stoppage losses, i.e. equipment failure, setup and adjustment, idling and minor stoppage, reduced speed, defects in the process, and reduced yield, were examined with the help of Pareto analysis. In addition, the actual availability (A), performance efficiency (PΕ) and quality rate (QR) measures, together with the complete OEE for each working day, week and month of the production line were shown. Findings The main goal of the study is to identify major stoppage losses, in order to examine and improve the overall equipment efficiency (OEE) of the ice cream production line through the application of an adequate management, i.e. TPM approach. Based on the obtained results, maintenance management strategy and production planning have been suggested to improve their maintenance procedures and the productivity as well. Originality/value The proposed method can be applied to each automated production system. The main benefits of this method are the improvement of productivity, quality enhancement of products, the reduction of sudden breakdowns and the cost of maintenance. Moreover, the analysis provides a useful perspective and helps managers/engineers make better decisions on the operations management of the line, and suggestions for improvement were proposed and will be implemented accordingly.

scholarly journals Using Haar-like Features and SVM Classifier for Quality Assurance in a Surgical Mask Production Line

2021 ◽  
Vol 10 (2) ◽  
pp. 148
Author(s):  
Laszlo Marak
Keyword(s):  
Quality Assurance ◽  
Feature Selection ◽  
Production Line ◽  
Low Cost ◽  
Classification Method ◽  
Svm Classifier ◽  
Production Lines ◽  
Camera System ◽  
Surgical Masks ◽  
Human Operators

With the recent increase for demand of surgical masks, the design and development of mask production lines has become an ever pressing issue. These production lines produce low cost high quantity products. As there are errors during the production, it is important to be able to detect invalid masks to assure that the produced masks are of consistent quality. Manual quality assurance using human operators is an error prone and a costly solution. In this article we describe an image classification method, which is using a low-cost Commercial Camera System and relies on Haar-like features combined with Maximum Relevance, Minimum Redundancy feature selection to detect the invalid masks at the end of the production process. The classification method consists of Preprocessing, Feature Selection and SVM Training. We have tested the method on a database of 150 000 images and it provides a high accuracy method which we use in the Production Line.

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