Design of pulse jet coolant delivery system for minimal quantity lubricant (IP MQL) operation

Minimum quantity lubrication (MQL) machining is one of the promising solutions to the requirement for reducing cutting fluid consumption. The work here describes MQL machining in a range of lubricant consumption of 2.0-2.355ml/s, which is between 10– 100 times lesser than the consumption usually adopted in industries. MQL machining in this range is called pulse jet coolant delivery system. A specially designed system, the IP MQL, was used for concentrating small amounts of lubricant onto the cutting interface. The performance of concentrated spraying of lubricant in pulse jet coolant delivery system design was simulated and compared with that of current ‘Pulse Jet MQL’ systems. The concentrated spraying of lubricant with a specially designed system was found to be effective in increasing tool life in the pulse jet coolant delivery system range

A Markov chain model for predicting Major League Baseball

In this report, we present a Markov chain model for predicting the scores and the winning team of Major League Baseball (MLB) games. We discuss how a baseball game can be viewed as an infinite horizon discrete-time Markov chain with finite state space. We demonstrate how standard Markov chain theory can be used to obtain analytical solutions for the expected runs and win probability in a given MLB matchup. We improve upon previous models by incorporating pitching and more complex baserunning, and then demonstrate the effect of these changes by comparing our model to historical data. We also discuss computational methods for solving the model. Finally, we test our model on games from the 2015 MLB season.Operations Research and Industrial Engineerin

Function-Based Mapping of Industrial Assistance Systems to User Groups in Production

Abstract By looking at the last few decades, industrial production has undergone great changes. Industry 4.0, also called the fourth industrial revolution, describes the change in the entire value chain through the digital networking of systems, machines, and products. In addition, product variety and complexity in assembly increased due to customization. Big Data Analytics, Internet of Things, Horizontal and Vertical Data Integration and Cyber-Physical Production Systems are just some examples of technologies that find their way from research into industrial practice. However, the most important resource is often neglected, when talking about industry: the human. When we look at companies, we find different types of personnel in production, each with different requirements and capabilities. Assistance systems can be used to counteract these new challenges and offer adequate support to each individual worker. In the past, much research has been done to develop new worker assistance systems, while the analysis of specific needs of user groups in production has been ignored. This paper presents a function-based mapping of industrial worker assistance systems to different user groups and proposes a method for selecting the most appropriate assistance system to each user group

Blockchain Feasibility Assessment - A Quantitative Approach

Industrial Engineerin

New Approaches for Monitoring Quality Control in the Clinical Laboratory

Industrial Engineerin

Study of the Basic Requirements for Success in an International Business-christian Missionary Venture

Industrial Engineerin

Developing a Certification Framework to Manufacture Patient-Specific Implants using Selective Laser Melting

Industrial Engineerin

Smart Maintenance System for Inner City Public Bus Services

Industrial Engineerin

Improved Quality of Continuous Flow Manufacturing through the Combination of Statistical Process Control and Conventional Computer Process Control

Industrial Engineerin

A Multi-Methodology System as IT Project Management Approach in South African Banking

Industrial Engineerin