Comparison between ANN and Multiple Linear Regression Models for Prediction of Warranty Cost

Nowadays, warranty has its own priority in business strategy for a manufacturer to protect their benefit as well as the intense competition between the manufacturers. In fact, warranty is a contract between manufacturer and buyer in which the manufacturer gives the buyer certain assurances as the condition of the property being sold. In industry, an accurate prediction of warranty costs is often counted by the manufacturer. Underestimation or overestimation of the warranty cost may have a high influence to the manufacturers. This paper presents a methodology to adapt historical maintenance warranty data with comparison between Artificial Neural Network (ANN) and multiple linear regression approach

Diagnosis of quality management systems using data analytics - A case study in the manufacturing sector

[EN] The main objective is to improve customer satisfaction by developing and testing a method to study quality management systems by analysing the key performance indicators of balanced scorecards in manufacturing environments. The methodology focuses on the identification and quantification of relationships between internal and external metrics that allow moving from performance measurement to effective performance management. It has been tested as a case study approach using real data from two complete years of the balanced scorecard of a leading manufacturing company. The results provided a new understanding of how the quality management system works that was used to make systemic and strategic decisions to improve the long-term performance of the company. Industry practitioners with a moderate level of data analytical skill can use it to help managers and executives improve management systems.Sánchez-Márquez, R.; Albarracín Guillem, JM.; Vicens Salort, E.; Jabaloyes Vivas, JM. (2020). Diagnosis of quality management systems using data analytics - A case study in the manufacturing sector. Computers in Industry. 115:245-263. https://doi.org/10.1016/j.compind.2019.10318324526311

Suppliers Evaluation and Selection: A Comprehensive Model to Minimize the Risk Associated with Quality and Delivery

This research focuses on one of the main steps in outsourcing, supplierevaluation and selection. The main contributions of this research were twofold.First, best practices in the supplier’s value stream were identified that directly orindirectly impact a supplier’s quality and delivery. Second, a comprehensivesupplier evaluation and selection model was developed based on the valuestream concept to minimize the risk associated with two very critical supplierselection factors, quality and on-time delivery.A survey was conducted to identify best practices. The outcome of the surveywas used to develop a computer based supplier evaluation model, which couldbe used in conjunction with other existing supplier selection factors, such as price and others, to select suppliers

HEAT PUMP AND AIR CONDITIONING GRADING SYSTEMS AND METHODS

An expectation module determines an expected average power consumption of a heat pump for a predetermined period as a function of indoor and outdoor temperatures of the building during the predetermined period. A difference module determines a power difference between an average power consumption of the heat pump during the predeter mined period and the expected average power consumption of the heat pump for the predetermined period. A grade determination module determines a grade of the heat pump for the predetermined period based on the power difference of the predetermined period. A reporting module generates a displayable report including the grade of the heat pump for the predetermined period

Warranty prediction during product development: Developing an event generation engine in an engineer-to-order environment

In order for manufacturing companies to stay competitive, it is necessary to drive warranty system improvements in terms of improved product reliability, improved service delivery efficiency and properly designed warranty policies. However, traditional methods for assessing warranty performance are not always sufficient to alert product development teams of the impending warranty issues. Furthermore, improved assessment methods are needed to aid product development teams make decisions related to the warranty performance of the product. The focus of this research was to develop a framework to integrate statistical inference methods and data mining techniques to create a warranty event generation framework. This was done on the context of an engineer-to-order product development environment. The objectives of this work were: (1) to develop an inference model for the integration of disparate data sources; (2) to demonstrate that multiple data streams can be conditioned for input into the above inference model; (3) to develop the above model and process in light of actual data. This thesis will report on the progress and challenges that have been made toward fulfilling these objectives. The thesis closes by outlining the future research agenda for developing a warranty event generation engine that can integrate data from disparate data sources

Telerobotic Sensor-based Tool Control Derived From Behavior-based Robotics Concepts

@font-face { font-family: TimesNewRoman ; }p.MsoNormal, li.MsoNormal, div.MsoNormal { margin: 0in 0in 0.0001pt; font-size: 12pt; font-family: Times New Roman ; }div.Section1 { page: Section1; } Teleoperated task execution for hazardous environments is slow and requires highly skilled operators. Attempts to implement telerobotic assists to improve efficiency have been demonstrated in constrained laboratory environments but are not being used in the field because they are not appropriate for use on actual remote systems operating in complex unstructured environments using typical operators. This work describes a methodology for combining select concepts from behavior-based systems with telerobotic tool control in a way that is compatible with existing manipulator architectures used by remote systems typical to operations in hazardous environment. The purpose of the approach is to minimize the task instance modeling in favor of a priori task type models while using sensor information to register the task type model to the task instance. The concept was demonstrated for two tools useful to decontamination & dismantlement type operations—a reciprocating saw and a powered socket tool. The experimental results demonstrated that the approach works to facilitate traded control telerobotic tooling execution by enabling difficult tasks and by limiting tool damage. The role of the tools and tasks as drivers to the telerobotic implementation was better understood in the need for thorough task decomposition and the discovery and examination of the tool process signature. The contributions of this work include: (1) the exploration and evaluation of select features of behavior-based robotics to create a new methodology for integrating telerobotic tool control with positional teleoperation in the execution of complex tool-centric remote tasks, (2) the simplification of task decomposition and the implementation of sensor-based tool control in such a way that eliminates the need for the creation of a task instance model for telerobotic task execution, and (3) the discovery, demonstrated use, and documentation of characteristic tool process signatures that have general value in the investigation of other tool control, tool maintenance, and tool development strategies above and beyond the benefit sustained for the methodology described in this work

Risk and trust management for online distributed system

This thesis investigated the problem of strategic manipulation of feedback attacks and proposed an approach that makes trust management systems sufficiently robust against feedback manipulation attacks. The new trust management system enables potential service consumers to determine the risk level of a service before committing to proceed with the transaction