Explore chapters and articles related to this topic
Exception Handling
Published in Rick Bitter, Taqi Mohiuddin, Matt Nawrocki, LabVIEW™ Advanced Programming Techniques, 2017
Rick Bitter, Taqi Mohiuddin, Matt Nawrocki
Exception handling is needed to manage the problems or errors that occur. It is a mechanism that allows a program to detect and possibly recover from errors during execution. Exception handling leads to more robust code by planning ahead for potential problems. Depending on the purpose of an application, the ability of an application to respond to unexpected events can be critical. Typical programs that are used by one person, at their desk may not need a lot in terms of robust performance. An application that is automating an assembly line that is producing hundreds of thousands of production units for revenue would benefit significantly from robust and sTable code. The implementation of an error handler increases the reliability of the code. It is difficult to prepare for all the possible errors that might occur, but preparing for the most probable errors can be done without much effort.
Exception Handling in Python
Published in Amartya Mukherjee, Nilanjan Dey, Smart Computing with Open Source Platforms, 2019
Amartya Mukherjee, Nilanjan Dey
In a standard Python application development scenario, the wrong syntax and semantics leads to exceptional condition in the program. This kind of error naturally causes during the time of execution of the program. When such error occurs, the program should take an appropriate safety measures so that the exception get handled to avoid the instantaneous program crash by the system. Exception handling mechanism is a convenient way to monitor and handle errors under certain special conditions. One can feel the need of exception handling to safeguard the program execution from the possible unknown behavior of the program code.
Development of machine tool communication method and its edge middleware for cyber-physical manufacturing systems
Published in International Journal of Computer Integrated Manufacturing, 2023
S M Nahian Al Sunny, Xiaoqing “Frank” Liu, Md Rakib Shahriar
Existing communication methods do not support direct operations of manufacturing machine tools over the Internet in a service-oriented and scalable manner, which is a major hindrance for manufacturing CPSs. MTComm, being an Internet-scale service-oriented communication method for exchanging manufacturing services over the Internet, addresses this issue. It allows manufacturers to acquire status data and perform machining operations of different types of machines situated in geographically different locations across the world remotely from web and cloud-based manufacturing applications through RESTful web services. Because of its agent-adapter based architecture and flexible interfacing options, MTComm can be used with modern network enabled machine tools as well as legacy manufacturing machines without network capability. As MTComm is a service-oriented method, additional services can be easily added if required. Adopting optimization strategies has greatly boosted MTComm’s performance and efficiency. Heterogeneous manufacturing resources can communicate with each other and participate in collaborative manufacturing through MTComm services. Thus, MTComm boosts machine interoperability and factory floor automation, and reduces human involvement in production processes. Through its robust Internetbased services, MTComm enable integration of CPS with other emerging technologies such as cloud manufacturing, IoT, edge/fog computing etc. The edge middleware can become a potential game-changing platform for future manufacturing by offloading iterative computational tasks to network edges and reducing burdens of central cloud servers, hence improving overall system scalability. Successful experiments in a CPMT further support MTComm’s potential for enhancing productivity and efficiency of today’s manufacturing systems. Additional researches and experiments with MTComm on traditional large-scale machine tools in diverse manufacturing environments are required before achieving its full potential in the industry. Future works may include development of more sophisticated optimization techniques, advanced security measures, further utilization edge computing capabilities, inclusion of exception handling and process planning, inclusion of big data analysis, deep and machine learning, rapid fault diagnosis and mitigation etc.