Statistical analysis of catalyst degradation in a semi-continuous chemical production process

2001 ◽  
Vol 15 (8) ◽  
pp. 665-683 ◽  
Author(s):  
Eleftherios Kaskavelis ◽  
Elaine Martin ◽  
Philip Jonathan ◽  
Julian Morris
Keyword(s):  
Statistical Analysis ◽  
Production Process ◽  
Chemical Production ◽  
Continuous Chemical

scholarly journals Statistical control of the production process of rolled products

2018 ◽  
Vol 20 (20) ◽  
pp. 26-31 ◽  
Author(s):  
Krzysztof Knop
Keyword(s):  
Statistical Analysis ◽  
Production Process ◽  
Normal Distribution ◽  
Control Charts ◽  
Statistical Control ◽  
Measurement Results ◽  
Corrective Actions ◽  
Fmea Method ◽  
The Stability ◽  
Level Of Risk

Abstract The article presents the results of the use of SPC tools, i.e. control charts and indicators of the qualitative capability to assess the stability and capability of the production process of rolled products - I-sections. Statistical analysis of the collected data regarding the selected feature of the analysed product - the width of the foot, and the normality of the distribution were done, which showed that the obtained distribution of measurement results is not a normal distribution. As a result, appropriate SPC procedures for non-normal distribution were used. The Pareto-Lorenzo diagram and FMEA method were also used to obtain information about the structure of non-conformities of the analysed product and the level of risk associated with them. This information was used to propose corrective actions and improve the production process of rolled products.

Using Lean-Sigma for the Integration of Two Products During a Ramp-Up Event

2020 ◽  
pp. 954-976
Author(s):  
Noe Alba-Baena ◽  
Francisco J. Estrada ◽  
Oswaldo Omar Sierra Torres
Keyword(s):  
Statistical Analysis ◽  
Production Process ◽  
Continuous Improvement ◽  
Six Sigma ◽  
Production Line ◽  
Lean Manufacturing ◽  
New Product ◽  
Quality Level ◽  
Manufacturing Environment ◽  
Improvement Methodologies

Keeping up the quality level in in a manufacturing environment has become an issue when trying to start the production of a new product which is in a ramp-up stage into a running production line ramp-down model. If production of the old model is ended too fast will make shortages in the customer supply, and will have excessive inventory numbers of the newer product. Trying the re-design in a production line to keep building the old model while incorporating the newer tends to create an undesirable impact on quality and productivity. Nowadays, continuous improvement methodologies like Lean and Six Sigma are used to solve this challenge. While Lean Manufacturing tends to be efficient for quick fixes, Six Sigma works better when there is plenty of time to conduct deeper statistical analysis. This chapter describes a combination of Lean Manufacturing speed with the Six Sigma analysis' power. Combined to maintain the quality and productivity of a production process during such conditions.

Improving Efficiency of Rolling Production by Predicting Negative Technological Events

2021 ◽  
Vol 410 ◽  
pp. 96-101
Author(s):  
Sergey M. Belskiy ◽  
Ivan I. Shopin ◽  
Andrey A. Safronov
Keyword(s):  
Statistical Analysis ◽  
Cold Rolling ◽  
Production Process ◽  
Rolling Mill ◽  
Production Efficiency ◽  
Cold Rolling Mill ◽  
Digital Service ◽  
Production Processes ◽  
Rolling Production ◽  
Basic Technology

Improving the production efficiency is the task with the increasing difficulty. Therefore, it is important to constantly expand the set of tools and perfect the methodology for improving the processes. Some of the losses associated with the negative technological events (breaks, drifting, etc.) are difficult to eliminate completely due to the complexity of making changes to the basic technology. But if you know in advance that the event will occur, you can significantly reduce the probability and consequences, thereby significantly improve the efficiency of the production process. Therefore, it is important to develop and introduce the applied approaches to forecasting the negative technological events in the production processes. This paper presents the method of the forecast-event statistical analysis of the cause-and-effect relationships. The technique was tested on the events of strip’s breakage during rolling at the cold rolling mill 1400 and strip’s drifting in the input storage of the continuous etching unit (CEU). Based on the presented methodology, the specialized digital service was developed and introduced in the production processes of the dynamo steels shop.

Sign in / Sign up

Export Citation Format

Share Document