scholarly journals A Multidimensional Data Flow Driven-Based Quality Fluctuation Evaluation for Manufacturing Process

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Sheng Hu ◽  
Bochao Dong
Keyword(s):  
Manufacturing Process ◽  
Network Architecture ◽  
Data Flow ◽  
Mode Analysis ◽  
Multidimensional Data ◽  
Entropy Measure ◽  
Evaluation Approach ◽  
Ensure Product Quality ◽  
Time Evaluation

Real-time evaluation quality fluctuation is an important way to ensure product quality in manufacturing process. This study proposes a multidimensional data flow driven-based quality fluctuation evaluation. Firstly, the multidimensional decomposition and transition mode analysis is carried out to reveal the essence of quality fluctuation. Then, the technique uses hierarchical network architecture to model the process, and quality fluctuation network is built to track fluctuation evolution trend; then, the node relative entropy measure is defined to statistically analyze the change of net-node state fluctuation. Finally, a case study is used to verify the proposed quality fluctuation evaluation approach.

Case Study and Fault Modeling for Wrong Redundancy Evaluation on DRAM Devices

2007 ◽  
Author(s):  
Martin Versen ◽  
Dorina Diaconescu ◽  
Jerome Touzel
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Fault Modeling ◽  
Mode Analysis ◽  
Root Cause ◽  
Failure Mode Analysis

Abstract The characterization of failure modes of DRAM is often straight forward if array related hard failures with specific addresses for localization are concerned. The paper presents a case study of a bitline oriented failure mode connected to a redundancy evaluation in the DRAM periphery. The failure mode analysis and fault modeling focus both on the root-cause and on the test aspects of the problem.

Implementation of MQTT protocol based network architecture for smart factory

2021 ◽  
pp. 095440542110144
Author(s):  
Chia-Shin Yeh ◽  
Shang-Liang Chen ◽  
I-Ching Li
Keyword(s):  
Machine Tool ◽  
Gesture Recognition ◽  
Manufacturing Process ◽  
Network Architecture ◽  
Information Management System ◽  
Edge Computing ◽  
Smart Factory ◽  
Smart Manufacturing ◽  
Industrial Iot ◽  
Computing Module

The core concept of smart manufacturing is based on digitization to construct intelligent production and management in the manufacturing process. By digitizing the production process and connecting all levels from product design to service, the purpose of improving manufacturing efficiency, reducing production cost, enhancing product quality, and optimizing user experience can be achieved. To digitize the manufacturing process, IoT technology will have to be introduced into the manufacturing process to collect and analyze process information. However, one of the most important problems in building the industrial IoT (IIoT) environment is that different industrial network protocols are used for different equipment in factories. Therefore, the information in the manufacturing process may not be easily exchanged and obtained. To solve the above problem, a smart factory network architecture based on MQTT (MQ Telemetry Transport), IoT communication protocol, is proposed in this study, to construct a heterogeneous interface communication bridge between the machine tool, embedded device Raspberry Pi, and website. Finally, the system architecture is implemented and imported into the factory, and a smart manufacturing information management system is developed. The edge computing module is set up beside a three-axis machine tool, and a human-machine interface is built for the user controlling and monitoring. Users can also monitor the system through the dynamically updating website at any time and any place. The function of real-time gesture recognition based on image technology is developed and built on the edge computing module. The gesture recognition results can be transmitted to the machine controller through MQTT, and the machine will execute the corresponding action according to different gestures to achieve human-robot collaboration. The MQTT transmission architecture developed here is validated by the given edge computing application. It can serve as the basis for the construction of the IIoT environment, assist the traditional manufacturing industry to prepare for digitization, and accelerate the practice of smart manufacturing.

scholarly journals Leveraging Machine-Learning for D2D Communications in 5G/Beyond 5G Networks

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 169
Author(s):  
Sherief Hashima ◽  
Basem M. ElHalawany ◽  
Kohei Hatano ◽  
Kaishun Wu ◽  
Ehab Mahmoud Mohamed
Keyword(s):  
Machine Learning ◽  
Network Architecture ◽  
D2d Communication ◽  
Neighbor Discovery ◽  
Research Directions ◽  
Fifth Generation ◽  
Research Activities ◽  
Comprehensive Survey ◽  
Network Overhead

Device-to-device (D2D) communication is a promising paradigm for the fifth generation (5G) and beyond 5G (B5G) networks. Although D2D communication provides several benefits, including limited interference, energy efficiency, reduced delay, and network overhead, it faces a lot of technical challenges such as network architecture, and neighbor discovery, etc. The complexity of configuring D2D links and managing their interference, especially when using millimeter-wave (mmWave), inspire researchers to leverage different machine-learning (ML) techniques to address these problems towards boosting the performance of D2D networks. In this paper, a comprehensive survey about recent research activities on D2D networks will be explored with putting more emphasis on utilizing mmWave and ML methods. After exploring existing D2D research directions accompanied with their existing conventional solutions, we will show how different ML techniques can be applied to enhance the D2D networks performance over using conventional ways. Then, still open research directions in ML applications on D2D networks will be investigated including their essential needs. A case study of applying multi-armed bandit (MAB) as an efficient online ML tool to enhance the performance of neighbor discovery and selection (NDS) in mmWave D2D networks will be presented. This case study will put emphasis on the high potency of using ML solutions over using the conventional non-ML based methods for highly improving the average throughput performance of mmWave NDS.

scholarly journals Waste reduction of polypropylene bag manufacturing process using Six Sigma DMAIC approach: A case study

2021 ◽  
Vol 8 (1) ◽  
pp. 1896419
Author(s):  
Muhammad Hamad Sajjad ◽  
Khawar Naeem ◽  
Muhammad Zubair ◽  
Qazi Muhammad Usman Jan ◽  
Sikandar Bilal Khattak ◽  
...  
Keyword(s):  
Six Sigma ◽  
Manufacturing Process ◽  
Waste Reduction

Process Signature Modeling for Tolerance Analysis

2010 ◽  
Vol 10 (2) ◽  
Author(s):  
R. Ascione ◽  
W. Polini ◽  
Q. Semeraro
Keyword(s):  
Concurrent Engineering ◽  
Manufacturing Process ◽  
Tolerance Analysis ◽  
Actual Surface ◽  
Contact Points ◽  
Geometric Tolerances ◽  
Systematic Pattern ◽  
Process Signature ◽  
Nominal Surface

Many well-known approaches exist in the literature for tolerance analysis. All the methods proposed in the literature consider the dimensional and the geometric tolerances applied to some critical points (contact points among profiles belonging to couples of parts) on the surface of the assembly components. These points are generally considered uncorrelated since the nominal surface is considered. Therefore, the methods proposed in the literature do not consider the actual surface due to a manufacturing process. Every manufacturing process leaves on the surface a signature, i.e., a systematic pattern that characterizes all the features machined with that process. The aim of the present work is to investigate the effects of considering the manufacturing signature in solving a tolerance stack-up function. A case study involving three parts has been defined and solved by means of a method of the literature, the variational method, with and without considering the correlation among the points of the same surface due to the manufacturing signature. This work represents a first step toward the integration of the design and the manufacturing in a concurrent engineering approach.

EVOLUTIONARY APPROACH IN PROCESS IMPROVEMENT — A CASE STUDY IN AUTO ELECTRICAL ALTERNATOR MANUFACTURING

2012 ◽  
Vol 11 (01) ◽  
pp. 27-50 ◽  
Author(s):  
A. J. JEGADHEESON ◽  
L. KARUNAMOORTHY ◽  
N. ARUNKUMAR ◽  
A. BALAJI ◽  
M. RAJKAMAL
Keyword(s):  
Process Improvement ◽  
Manufacturing Process ◽  
Welding Process ◽  
Evolutionary Approach ◽  
Geometrical Analysis ◽  
Designed Experiments ◽  
Self Development ◽  
Riveting Process

Evolution is "understanding and overcoming current constraints in small steps toward optimum." "Understanding" requires elucidation of facts and corroborating theories that can explain those facts in a coherent manner. "Overcoming" requires self-development to suit the environment. In this paper, a case study about how a manufacturing process is improved in terms of productivity and quality using evolutionary improvements is explained. Here "Understanding" is achieved through use of Shainin Technique, PM analysis, Affinity Diagram, and the engineer's ingenuity, along with Relations diagram. "Overcoming" is achieved through Geometrical Analysis and Designed Experiments. The Study has set a new benchmark in the Stator riveting process by proving it can yield the desired results, and the need to adapt welding process is avoided.

Case Study Approach for Information-Integration of Material Handling

1991 ◽  
Author(s):  
Bipin Chadha ◽  
R. E. Fulton ◽  
J. C. Calhoun
Keyword(s):  
Case Studies ◽  
Information Integration ◽  
Data Flow ◽  
Database Management System ◽  
Commercial Application ◽  
Case Study Approach ◽  
Study Approach ◽  
Flow Diagrams ◽  
Data Flow Diagrams

Abstract Information-Integration is vital for keeping manufacturing operations competitive. A case study approach has been adopted to better understand the role of information in integrated manufacturing. Information is now considered a corporate asset. Creation, processing, movement, and security of information is therefore as important as that of the products/services of an enterprise. The case studies have helped in identifying the issues involved in developing an information system and supporting software framework for a manufacturing enterprise. The case studies have helped in refining an integration model, and identifying the characteristics desirable in modeling methodologies and tools. This paper describes a case study dealing with integrated manufacture of optical fiber products. A phased development and implementation approach was adopted where a small, manageable slice of the system is considered for the case study followed by functional modeling (IDEF0) and data flow modeling (Data Flow Diagrams). This identifies the pieces of information of interest. The information relationships are modeled using Extended Entity Relationship (EER) diagrams which are then mapped on to a relational model. The relational tables thus obtained were implemented on a commercial Database Management System. The functional constraints and application interfaces were then built using SQL and commercial application interface tools. The sections in the paper describe the functional models, data flow diagrams, EER diagrams, relational database design, and user/application interfaces developed for the system. Implementation experiences and observations are discussed followed by plans for the next phase of the system.

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