Towards a realtime knowledge-based simulation system for diagnosing machine tool failure

2002 ◽  
Author(s):  
S. Manivannan ◽  
J. Banks
Keyword(s):  
Machine Tool ◽  
Simulation System ◽  
Tool Failure ◽  
Knowledge Based

scholarly journals Continuous modelling of machine tool failure durations for improved production scheduling

2020 ◽  
Vol 14 (2) ◽  
pp. 207-215
Author(s):  
B. Denkena ◽  
M.-A. Dittrich ◽  
L. Keunecke ◽  
S. Wilmsmeier
Keyword(s):  
Machine Tool ◽  
Production Scheduling ◽  
Tool Failure

UNDERSTANDING SOFTWARE PRODUCTIVITY: TOWARDS A KNOWLEDGE-BASED APPROACH

1991 ◽  
Vol 01 (03) ◽  
pp. 293-321 ◽  
Author(s):  
WALT SCACCHI
Keyword(s):  
Modeling And Simulation ◽  
State Of The Art ◽  
Simulation System ◽  
Knowledge Based ◽  
Current State ◽  
Software Productivity ◽  
Productivity Modeling

What affects software productivity and how do we improve it? This report examines the current state of the art in understanding and measuring software productivity. In turn, it describes a framework for understanding software productivity, identifies some fundamentals of measurement, surveys selected studies of software productivity, and identifies variables that affect software productivity. Then, a radical alternative to current approaches is suggested: to construct, evaluate, deploy, and evolve a knowledge-based "software productivity modeling and simulation system."

Smart Machining Simulation Based on High-Level Data

2010 ◽  
Author(s):  
Aini Zuhra Abdul Kadir ◽  
Xun Xu
Keyword(s):  
Machine Tool ◽  
Input Data ◽  
Simulation System ◽  
Machining Process ◽  
Machining Simulation ◽  
Time Data ◽  
Machining Processes ◽  
Level Data ◽  
G Code ◽  
High Level

The main objective of any machining simulation system is to produce a model that can reveal or mimic the real machining process as accurately as possible. Current simulation systems often use G-code or CL data as input that has inherent drawbacks such as vendor-specific nature, incomplete data, irreversible data conversions and lack of accuracy. These limitations hinder the development of a ‘trustworthy’ simulation system. Hence, there is a need for higher-level input data that can assist with accurate simulation for machining processes. There is also a need to take into account of true behaviour and real-time data of a machine tool. The paper presents a ‘near-real simulation’ solution for more accurate results. STEP-NC is used as the input data as it provides a more complete data model for machining simulations. Data from the machine tool is captured by means of sensors to provide true values for machining simulation purposes. The outcome of the research provides a smart and better informed simulation environment. The paper reviewed some of the current simulation approaches, discussed input data sources for smart simulation system and proposed near-real simulation system architecture.

scholarly journals Development of Machine Tool Operation Simulation System by VR

2020 ◽  
Vol 2020 (0) ◽  
pp. S14307
Author(s):  
Shuma ONODERA ◽  
Yoshitaka MORIMOTO ◽  
Akio HAYASHI
Keyword(s):  
Machine Tool ◽  
Simulation System
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