Achieving Process Efficiency and Stability in Serial Production Through an Innovative Service System Based on Predictive Maintenance

2018 ◽  
pp. 657-666 ◽  
Author(s):  
Max Busch ◽  
Johan de Lange ◽  
Christoph Kelzenberg ◽  
Günther Schuh
Keyword(s):  
Service System ◽  
Predictive Maintenance ◽  
Process Efficiency ◽  
Serial Production

scholarly journals Integrating Predictive Maintenance in Adaptive Process Scheduling for a Safe and Efficient Industrial Process

2021 ◽  
Vol 11 (11) ◽  
pp. 5042
Author(s):  
Orhan Can Görür ◽  
Xin Yu ◽  
Fikret Sivrikaya
Keyword(s):  
Planning Process ◽  
Industrial Process ◽  
Conveyor Belt ◽  
Predictive Maintenance ◽  
Process Efficiency ◽  
Support Vector ◽  
Small Scale ◽  
Process Scheduling ◽  
Adaptive Process ◽  
Autonomous Planning

Predictive maintenance (PM) algorithms are widely applied for detecting operational anomalies on industrial processes to schedule for a maintenance intervention before a possible breakdown; however, much less focus has been devoted to the use of such prognostics in process scheduling. The existing solutions mostly integrate preventive approaches to protect the machines, usually causing downtimes. The premise of this study is to develop a process scheduling mechanism that selects an acceptable operating condition for an industrial process to adapt to the predicted anomalies. As PM is largely a data-driven approach (hence, it relies on the setup), we first compare different PM approaches and identify a one-class support vector machine (OCSVM) as the best performing option for the anomaly detection on our setup. Then, we propose a novel pipeline to integrate maintenance predictions into a real-time, adaptive process scheduling mechanism. According to the abnormal readings, it schedules for the most suitable operation, i.e., optimizing for machine health and process efficiency, toward preventing breakdowns while maintaining its availability and operational state, thereby reducing downtimes. To demonstrate the pipeline on the action, we implement our approach on a small-scale conveyor belt, utilizing our Internet of Things (IoT) framework. The results show that our PM-based adaptive process control retains an efficient process under abnormal conditions with less or no downtime. We also conclude that a PM approach does not provide sufficient efficiency without its integration into an autonomous planning process.

Performance Analysis on Eco-friendly Machining of Ti6Al4V using Powder Mixed with Different Dielectrics in WEDM

2020 ◽  
Vol 17 (3) ◽  
pp. 8128-8139
Author(s):  
S. Chakraborty ◽  
S. Mitra ◽  
D. Bose
Keyword(s):  
Metal Removal ◽  
Removal Rate ◽  
Machining Process ◽  
Process Efficiency ◽  
Machining Parameters ◽  
Dielectric Fluids ◽  
High Emission ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process

The recent scenario of modern manufacturing is tremendously improved in the sense of precision machining and abstaining from environmental pollution and hazard issues. In the present work, Ti6Al4V is machined through wire EDM (WEDM) process with powder mixed dielectric and analyzed the influence of input parameters and inherent hazard issues. WEDM has different parameters such as peak current, pulse on time, pulse off time, gap voltage, wire speed, wire tension and so on, as well as dielectrics with powder mixed. These are playing an essential role in WEDM performances to improve the process efficiency by developing the surface texture, microhardness, and metal removal rate. Even though the parameter’s influencing, the study of environmental effect in the WEDM process is very essential during the machining process due to the high emission of toxic vapour by the high discharge energy. In the present study, three different dielectric fluids were used, including deionised water, kerosene, and surfactant added deionised water and analysed the data by taking one factor at a time (OFAT) approach. From this study, it is established that dielectric types and powder significantly improve performances with proper set of machining parameters and find out the risk factor associated with the PMWEDM process.

Reforming Pension Service System for Small Businesses

2016 ◽  
Vol 17 (1) ◽  
pp. 131-154
Author(s):  
김대환 ◽  
Joo-Ho Sung ◽  
정무섭 ◽  
김재현
Keyword(s):  
Small Businesses ◽  
Service System

A Study on the Core Competency for Product-Service System

2015 ◽  
Vol 29 (2) ◽  
pp. 171-195 ◽  
Author(s):  
Hong, Yong-pyo ◽  
Young Jun Kim
Keyword(s):  
Service System ◽  
Core Competency ◽  
Product Service System ◽  
The Core ◽  
Product Service

The Convergence between Predictive Maintenance and Augmented Reality to Aid Renewable Energy Equipment Availability

2014 ◽  
Vol 2 (5) ◽  
pp. 152
Author(s):  
José Manuel Torres Farinha ◽  
Inácio Adelino Fonseca ◽  
Rúben Silva Oliveira ◽  
Fernando Maciel Barbosa
Keyword(s):  
Renewable Energy ◽  
Augmented Reality ◽  
Predictive Maintenance ◽  
Equipment Availability ◽  
Energy Equipment

A Queueing Model of a Multi-Service System with State-Dependent Distribution of Resources for Each Class of Calls

2014 ◽  
Vol E97.B (8) ◽  
pp. 1592-1605 ◽  
Author(s):  
Slawomir HANCZEWSKI ◽  
Maciej STASIAK ◽  
Joanna WEISSENBERG
Keyword(s):  
Service System ◽  
Queueing Model ◽  
State Dependent ◽  
Distribution Of Resources
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