Automation of Data Collection for Measuring The Quality of E-Commerce

The research aims to help managers in information gathering web log visitors based on traffic data, building automation data for determining the needs of e-Commerce extensibility, and design of information systems in the process of database interaction diagrams to show the control chart. Web monitoring is not so complex that requires a variety of tools (tools / applications / programs). Data collection in the form of traffic data and transaction data obtained automation. Data collected by the web application traffic and data traffic of e-Commerce transactions themselves. For a company whose goal is not just appear and serve customers, but is able to know the customer desires and business growth observed, this method is very suitable for monitoring quality control chart diagram shown in the form on page E-Commece it. Automation of data collection occurred in real time on information systems, so that the extensibility of e-Commerce report can be continuously monitored. The results demonstrate the extensibility of information systems such as e-Commerce can be applied to other e-Commerce

The development of egg hatching and storage machines equipped with cooling and heating systems and iot

The development of egg hatching and storage machines equipped with cooling and heating systems and IoT was for helping chicken breeders to address the issue of chicken production shortages. To produce large numbers of poultry production, eggs hatching is one of the major step that needs to pay attention to. There are several reasons why egg hatching process fails, such as lack of care by hen, eaten by rooster, and unsuitable hatching environment and temperature. In addition, if the eggs are not incubated within 1 week, the eggs will be damaged having producing a hatching machine and egg storage can help the chicken breeders to produce a better amount of chicken production. Internet of Things (IoT) elements such as the Arduino and Blynk are also used to make this egg hatching and storage machine attractive and to meet the needs and requirements of users. The objectives of this study were to design, develop and evaluate the functionality of egg hatching and storage machines in combination with cooling and heating systems along with IoT. Methodology is a technique and method that incorporates methods and approaches used to achieve the objectives and objectives of the study. The model used is the ADDIE model which consists of 5 phases namely Analysis, Design, Development, Implementation, and Evaluation. This product has received expert confirmation in terms of design and functionality. The results show that the egg hatching and storage machine is well developed and can attract users when using this hatching and storage machine

Cost reduction using process analysis in company PEGRES obuv s.r.o.

Firma PEGRES obuv s.r.o. se již delší dobu potýká se stagnací v oblasti plánování a řízení výroby. Některé podnikové procesy jsou nyní značně zastaralé a v aktuálních podmínkách již neefektivní. Cíl práce je snížení nákladů s využitím procesní analýzy. Pro dosažení tohoto cíle bude provedena analýza současného stavu zastaralých procesů a budou popsány vybrané metody řízení výroby, které jsou svou povahou relevantní pro výrobu obuvi. Výstupem práce je sada doporučení a návrhů na změny v existujících procesech. Vybrané návrhy budou v prostředí firmy implementovány a práce zahrne zhodnocení výsledků po zavedení těchto změn.Company PEGRES obuv s.r.o. has been long time struggling with stagnation in production planning and control. Some of the internal processes are now obsolete and in current conditions no longer effective. The goal of the paper is to reduce the costs using process analysis. To achieve this goal, analysis of the current state of outdated processes will be performed, followed by description of selected methods of production management, which by their nature are relevant to the production of the shoes. Output of the work is a set of recommendations and proposals for changes to existing processes. Selected proposals will be implemented in the company and paper will include evaluation of results after the implementation of these changes.

A Preliminary Study of Applying Lean Six Sigma Methods to Machine Tool Measurement

Many manufacturers aim to increase their levels of high-quality production in order to improve their market competitiveness. Continuous improvement of maintenance strategies is a key factor to be capable of delivering high quality products and services on-time with minimal operating costs. However, the cost of maintaining quality is often perceived as a non-added-value task. Improving the efficiency and effectiveness of the measurement procedures necessary to guarantee accuracy of production is a more complex task than many other maintenance functions and so deserves particular analysis. This paper investigates the feasibility of producing a concise yet effective framework that will provide a preliminary approach for integrating Lean and Six Sigma philosophies to the specific goal of reducing unnecessary downtime on manufacturing machines while maintaining its ability to machine to the required tolerance. The purpose of this study is to show how a Six Sigma infrastructure is used to investigate the root causes of complication occurring during the machine tool measurement. This work recognises issues of the uncertainty of data, and the measurement procedures in parallel with the main tools of Six Sigma’s Define-Measure-Analyse-Improve-Control (DMAIC). The significance of this work is that machine tool accuracy is critical for high value manufacturing. Over-measuring the machine to ensure accuracy potentially reduces production volume. However, not measuring them or ignoring accuracy aspects possibly lead to production waste. This piece of work aims to present a lean guidance to lessen measurement uncertainties and optimise the machine tool benchmarking procedures, while adopting the DMAIC strategy to reduce unnecessary downtime

Economic Design of X-bar control chart using particle swarm optimization

Control chart is the most widely used tools for statistical process control. For detecting shift in process mean, chart is the simplest and most commonly used. Control chart should be designed economically in order to achieve minimum quality control costs. The major function of control chart is to detect the occurrence of assignable causes so that the necessary corrective action can be taken before a large quantity of nonconforming product is manufactured. The control chart dominates the use of any other control chart technique if quality is measured on a continuous scale. The design of a control chart refers to the selection of three parameters i.e., sample size, width of control limit, and interval between samples. Economic design of control chart has gained considerable importance in providing better quality of end products to customer at less cost. In the present work, a computer programme in C language based on a non-traditional optimization technique namely particle swarm optimization has been developed for the economic design of the control chart giving the optimum values of the sample size, sampling interval and width of control limits such that the expected total cost per hour is minimized. The results obtained are found to be better compared to that reported in the literature

Discussion of Parabolic Mask for Cumulative Sum Control Charts

In this paper we will discuss the use of parabolic control limits for cumulative sum (Cusum) control charts and an approach to correct the average run length (ARL) problem that may result from using a three sigma parabolic mask. Result of a simulation study will be reported to correct this problem

A quality management based on the Quality Model life cycle

Managing quality is a hard and expensive task that involves the execution and control of processes and techniques. For a good quality management, it is important to know the current state and the objective to be achieved. It is essential to take into account with a Quality Model that specifies the purposes of managing quality. QuEF (Quality Evaluation Framework) is a framework to manage quality in MDWE (Model-driven Web Engineering). This paper suggests managing quality but pointing out the Quality Model life cycle. The purpose is to converge toward a quality continuous improvement by means of reducing effort and time.Ministerio de Ciencia e Innovación TIN2010-20057-C03-02Ministerio de Ciencia e Innovación TIN 2010-12312-EJunta de Andalucía TIC-578

A Multivariate Quality Control Approach for Automated Manufacturing Systems

In today\u27s competitive manufacturing environment, effective and practical statistical quality control approaches are essential. A successful process control approach needs to provide on line real time monitoring of quality related characteristics. No longer acceptable is an approach that analyzes quality related data only after the product is produced. A statistical process control approach that monitors the process during production and that reports trouble spots before bad products are made is necessary in an automated manufacturing environment. An automated manufacturing environment is characterized by high volume production runs and short production cycles. Traditional statistical process control approaches are not capable of dealing with these challenges and cannot keep up with the pace of automated manufacturing. In this research, a statistical process control approach for automated manufacturing systems is developed. The research demonstrates and evaluates a multivariate cumulative sum control scheme (CUSUM) to a set of standardized data collected from an actual production line. Results indicate that the statistical process control approach developed is able to detect small variations in the process quickly and effectively. Furthermore, the approach is capable of monitoring several quality characteristics simultaneously in real time. Quality control for short production runs is also addressed in this research