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\title{Implementation of Control Chart for Statistical Process Control Considering Temperature and Humidity Effect in Synthetic Staple Fiber Industry}
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             \author[1]{Abu Md.  Saifuddoha}

             \author[2]{Md. Saiful  Islam}

             \affil[1]{  Khulna University of Engineering and Technology}

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\date{\small \em Received: 11 December 2018 Accepted: 4 January 2019 Published: 15 January 2019}

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\begin{abstract}
        


The purpose of this paper is to identify various fluctuations of temperature and humidity effecting synthetic staple fibers quality such as strength and tenacity as a final finished product and address these fluctuations effect through implementation of control chart for establishing statistical process control over synthetic fiber production process. Critical observations and test results are analyzed to show that temperature and humidity effect over synthetic staple fiber quality such as strength and tenacity. Establishing statistical process control in the synthetic staple fiber-processing sector is one key to improving the quality of synthetic staple fiber sector considering temperature and humidity effect. The resultant variations and fluctuations are addressed through categorizing various kinds of fiber by implementing control chart. The paper addresses the fluctuations and variations of synthetic fiber quality such as strength and tenacity due to temperature and humidity effect in the production processing of synthetic fiber industry, using control chart as an approach to solve these variations which was hardly attempted before. Strength and tenacity individually prioritized to reduce fluctuations into the entire production process system.

\end{abstract}


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\let\tabcellsep& 	 	 		 
\section[{Introduction}]{Introduction}\par
he manufacture of synthetic fibers represents a huge industry, both in the Bangladesh and worldwide. In the twenty first century, the dollar value of synthetic fibers was roughly \$100 billion in the worldwide. We sometimes forget how much of these fibers we consume, especially since the appeal of "natural" fibers of cotton and wool has grown in recent years. Despite questions of aesthetics and taste, there should continue to be a significant demand for synthetic fibers, in large part because these fibers can be tailormade to provide specific properties that natural fibers cannot provide.\par
Statistical methods play a vital role in the quality improvement process in manufacturing and service industries. Control charts are used to check for process stability. In this context, a process is said to be "in statistical control" if the probability distribution representing the quality characteristic is constant over time. If there is some change over time in this distribution, the process is said to be "out of control."\par
Author ? ?: Student of Department of industrial Engineering and management, Khulna University of Engineering and Technology, Fulbariget, Khulna-9203, Bangladesh. e-mails: saifsf08@gmail.com, saifuliem@gmail.com As students of production engineering, we are interested in implementing control chart to improve synthetic fibers quality because the process involves several fundamental aspects of production and quality control engineering. The goal here to address the fluctuations and variations of synthetic fiber quality such as strength and tenacity due to temperature and humidity effect in the production processing of synthetic fiber industry, using control chart as an approach to solve these variations which was hardly attempted before. 
\section[{II.}]{II.} 
\section[{Synthetic Fiber Manufacturing}]{Synthetic Fiber Manufacturing}\par
True synthetics are products of the polymerization of smaller chemical units into long-chain molecular polymers. Fibers are formed by forcing a viscous fluid or solution of the polymer through the small orifices of a spinneret and immediately solidifying or precipitating the resulting filaments. Synthetic fibers are produced typically by two easily distinguishable methods, melt spinning and solvent spinning. \hyperref[b0]{[1]} For the common spinning of filaments in the finished range of about 0.1 -2 tex spinnerets of a diameter 0.1-0.7 mm for melt spinning. Melt spinning is done for most polymers (PET, PP) between 240°C and 320°C. \hyperref[b1]{[2]} Polyester fiber spinning is done almost exclusively with extruders, which feed the molten polymer under pressure through the spinnerets. Filament solidification is induced by blowing the filaments with cold air at the top of the spin cell. The filaments are then led down the spin cell through a fiber finishing application, from which they are gathered into tow, hauled off, and coiled into spinning cans. Depending on the desired product, post-spinning operations vary but may include lubrication, drawing, crimping, heat setting, and stapling.  
\section[{G}]{G}\par
Denier /?or den (abbreviated D), a unit of measure for the linear mass density of fibers, is defined as the mass in grams per 9000 meters. The denier is based on a natural reference: a single strand of silk is approximately one denier; a 9000-meter strand of silk weighs about one gram. Denier = (weight of fiber ×9000) ÷ (number of fiber× length of fiber)\par
Tex is a unit of measure for the linear mass density of fibers, yarns and thread and is defined as the mass in grams per 1000 meters. The unit code is "tex". When measuring objects that consist of multiple fibers, the term "filament tex" is sometimes used, referring to the mass in grams per 1000 meters of a single filament. Tex is used for measuring fiber size in many products, including cigarette filters, optical cable, yarn and fabric. \hyperref[b4]{[5]} Tex = Denier ÷ 9\par
(2)\par
The rate of crystallization depends on the molecular weight, the history of the PP melt, and the temperature and humidity. In the Spinneret capillary there is a minor pre orientation. The major portion of the orientation is created from the outside filament portion that solidifies first in the border phase between the liquid inside portion and the solidified filament portion. \hyperref[b1]{[2]} The temperature effect can described below:\par
? A hot shroud below the spinneret lengthens the freezing zone, delays the filament thinning and cooling, and increases the yarn tension. ? Cooler quench air and/or higher quench air velocity result in faster filament thinning and higher yarn tension. ? Higher spinneret temperatures result in higher yarn temperatures along the first part of the filament axis, reduce the yarn tension. ? Higher throughputs per spinneret with constant take-up speed increase the cooling time and cooling zone with little influence on the yarn tension.\par
The temperature and humidity effect during polypropylene (pp) spinning is studied at a synthetic fiber manufacturing company named Dird Polytex Limited. Here, the tenacity of the PP fiber increases due to lower temperature and humidity during winter from October to March and the tenacity of the PP fiber decreases due to higher temperature and humidity during summer from April to September. The data was taken from July, 2014 to May, 2015 of average monthly temperature, humidity and tenacity.  
\section[{Control Chart}]{Control Chart}\par
Control chart is graphical representation of the collected information. A control chart indicates whether a process is in control or out of control. It determines processes variability and detects unusual variations taking place in a process. It provides information about the selection of process and setting of tolerance limits. There are two types of control charts. They are variable and attribute chart. Variable charts involve the measurement of the job dimensions whereas an attribute chart only differentiates between a defective item and a non-defective item. \hyperref[b5]{[6]} a) X-bar and R chart X-bar and R chart is one kind of variable chart. X-bar chart shows changes in process and is affected by changes in process variability. R chart secures information in establishing or modifying processes, inspection procedures. X-bar and R-bar chart when  \hyperref[tab_1]{1} shows monthly tenacity value of PP white fiber which has been recorded and among them randomly eight days value have been taken for implementation of x-bar and r chart. Warning limit is the two third portion of the corresponding control limit.  IV. 
\section[{Result Analysis}]{Result Analysis}\par
Here fig. \hyperref[fig_2]{2} and 3 depict x bar and r chart in which fig. \hyperref[fig_2]{2} shows 4 points below lower limit and 1 point above upper limit and fig. \hyperref[fig_3]{3} shows 4 points below lower limit and 2 points above upper limit. That means both x bar and r chart shows the process is out of control.\par
As the corresponding figure shows the process is out of control, this happens due to variation of temperature and humidity across the year 2014-15. The weather phenomena cannot be controlled so to solve this problem. A proper grading system is developed for different quality fibers in table 3 according to the x bar chart.  
\section[{Conclusion}]{Conclusion}\par
There is significant effect of temperature and humidity over synthetic staple fiber production process. Control chart is applied to categorize various kinds of synthetic staple fiber considering temperature and humidity effect for establishing statistical quality control over synthetic fiber production process. The paper addresses the fluctuations and variations of synthetic fiber quality such as strength and tenacity due to temperature and humidity effect in the production processing of synthetic fiber industry. 
\section[{APPENDIX.A}]{APPENDIX.A}\begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-2.png}
\caption{\label{fig_0}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{1}\includegraphics[]{image-3.png}
\caption{\label{fig_1}Figure 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2}\includegraphics[]{image-4.png}
\caption{\label{fig_2}Figure 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3}\includegraphics[]{image-5.png}
\caption{\label{fig_3}Figure 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-6.png}
\caption{\label{figure6}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{P{0.1255420054200542\textwidth}P{0.0679539295392954\textwidth}P{0.0679539295392954\textwidth}P{0.0679539295392954\textwidth}P{0.06910569105691057\textwidth}P{0.08868563685636856\textwidth}P{0.0679539295392954\textwidth}P{0.06910569105691057\textwidth}P{0.0679539295392954\textwidth}P{0.08868563685636856\textwidth}P{0.06910569105691057\textwidth}}
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{Tenacity ( cN/tex )}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
Month\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep Day 1\tabcellsep Day 2\tabcellsep Day 3\tabcellsep Day 4\tabcellsep Day 5\tabcellsep Day 6\tabcellsep Day 7\tabcellsep Day 8\tabcellsep X Bar\tabcellsep Range\\
July,14\tabcellsep 39.49\tabcellsep 47.66\tabcellsep 46.91\tabcellsep 38.33\tabcellsep 45.22\tabcellsep 42.71\tabcellsep 43.75\tabcellsep 45.44\tabcellsep 43.69\tabcellsep 7.11\\
August,14\tabcellsep 37.73\tabcellsep 42.89\tabcellsep 35.17\tabcellsep 36.62\tabcellsep 38.72\tabcellsep 42.81\tabcellsep 45.41\tabcellsep 43.62\tabcellsep 40.37\tabcellsep 8.79\\
September ,14\tabcellsep 36.1\tabcellsep 39.05\tabcellsep 43.37\tabcellsep 43.93\tabcellsep 44.94\tabcellsep 37.38\tabcellsep 43.27\tabcellsep 43.54\tabcellsep 41.45\tabcellsep 8.84\\
October,14\tabcellsep 42.64\tabcellsep 45.29\tabcellsep 42.88\tabcellsep 46.28\tabcellsep 47.61\tabcellsep 43.73\tabcellsep 48.95\tabcellsep 41.79\tabcellsep 44.90\tabcellsep 5.82\\
November,14\tabcellsep 41.25\tabcellsep 48.77\tabcellsep 42.86\tabcellsep 45.00\tabcellsep 43.18\tabcellsep 45.98\tabcellsep 50.22\tabcellsep 45.41\tabcellsep 45.33\tabcellsep 8.97\\
December,14\tabcellsep 45.77\tabcellsep 40.03\tabcellsep 43.24\tabcellsep 44.96\tabcellsep 49.56\tabcellsep 44.34\tabcellsep 43.49\tabcellsep 48.31\tabcellsep 44.96\tabcellsep 9.53\\
January,15\tabcellsep 45.69\tabcellsep 41.41\tabcellsep 49.25\tabcellsep 45.93\tabcellsep 46.51\tabcellsep 49.97\tabcellsep 45.44\tabcellsep 41.41\tabcellsep 45.70\tabcellsep 8.56\\
February,15\tabcellsep 49.47\tabcellsep 46.45\tabcellsep 55.17\tabcellsep 49.93\tabcellsep 48.92\tabcellsep 43.46\tabcellsep 45.22\tabcellsep 41.79\tabcellsep 47.55\tabcellsep 13.38\\
March,15\tabcellsep 44.38\tabcellsep 39.45\tabcellsep 37.39\tabcellsep 38.62\tabcellsep 43.33\tabcellsep 38.48\tabcellsep 38.02\tabcellsep 38.93\tabcellsep 39.83\tabcellsep 6.99\\
April,15\tabcellsep 35.94\tabcellsep 26.69\tabcellsep 31.06\tabcellsep 29.14\tabcellsep 30.4\tabcellsep 32.6\tabcellsep 39.62\tabcellsep 40.78\tabcellsep 33.28\tabcellsep 14.09\\
May,15\tabcellsep 31.78\tabcellsep 34.3\tabcellsep 34.3\tabcellsep 36.43\tabcellsep 34.1\tabcellsep 34.23\tabcellsep 29.64\tabcellsep 36.3\tabcellsep 33.89\tabcellsep 6.79\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep X Double Bar\tabcellsep R Bar\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep 44.29\tabcellsep 8.79\end{longtable} \par
 
\caption{\label{tab_1}Table 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2} \par 
\begin{longtable}{P{0.11184210526315788\textwidth}P{0.5681578947368421\textwidth}P{0.17\textwidth}}
Bar Chart Type\tabcellsep Description\tabcellsep Formula\\
\tabcellsep Upper Control Limit\tabcellsep 46.80\\
X bar\tabcellsep Upper Warning Limit Lower Warning Limit\tabcellsep 45.96 42.62\\
\tabcellsep Lower Control Limit\tabcellsep 41.79\\
Range\tabcellsep Upper Control Limit Lower Control Limit\tabcellsep 10.53 8.53\\
1\tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_2}Table 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{P{0.5022727272727273\textwidth}P{0.16903409090909088\textwidth}P{0.04105113636363636\textwidth}P{0.13764204545454545\textwidth}}
Fiber Quality Limit\tabcellsep Tenacity(cn/tex)\tabcellsep Fiber Grade\tabcellsep Fiber Quality\\
Above upper limit\tabcellsep >46.8\tabcellsep A\tabcellsep Very Good\\
Between upper warning limit to upper limit\tabcellsep 45.96-46.8\tabcellsep B\tabcellsep Good\\
Between upper warning limit and mean\tabcellsep 44.29-45.96\tabcellsep C\tabcellsep Average\\
Between mean to lower warning limit\tabcellsep 42.62-44.29\tabcellsep D\tabcellsep Below Average\\
Between lower warning limit to lower limit\tabcellsep 41.79-42.62\tabcellsep E\tabcellsep Bad\\
Below lower limit\tabcellsep <41.79\tabcellsep F\tabcellsep Very Bad\end{longtable} \par
 
\caption{\label{tab_3}Table 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{} \par 
\begin{longtable}{P{0.85\textwidth}}
V.\\
XUCL\\
XUWL\\
Mean\\
X bar\\
XLWL\\
XLCL\end{longtable} \par
 
\caption{\label{tab_4}cn/tex) Name of Month}\end{figure}
 		 		\backmatter  			  				\begin{bibitemlist}{1}
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\bibitem[Collier (1970)]{b4}\label{b4} 	 		 			Ann M Collier 		.  		 ISBN 0-08-018056-6.  		\textit{A Handbook of Textiles},  				1970. January 2009. Pergamon Press. p. 258.  	 
\bibitem[Fourne and Hanser; Cincinnati Hanser Gardner (ed.) ()]{b1}\label{b1} 	 		 			Franz Fourne 		.  		\textit{Synthetic fibers},  				 			: Hanser; Cincinnati,  			/ Hanser,  			Gardner 		 (ed.)  		 (Munich)  		1998.  	 
\bibitem[Haynes ()]{b3}\label{b3} 	 		 			Williams Haynes 		.  		\textit{XVII: New Fibres: New Fabrics". This Chemical Age. London: Secker and Warburg},  				1946. p. 217.  	 
\bibitem[Industrial Process Profiles For Environmental Use -Chapter 11 -The Synthetic Fiber Industry, EPA Contract No. 68-02-1310 Aeronautical Research Associates of Princeton (1976)]{b2}\label{b2} 	 		‘Industrial Process Profiles For Environmental Use -Chapter 11 -The Synthetic Fiber Industry, EPA Contract No. 68-02-1310’.  	 	 		\textit{Aeronautical Research Associates of Princeton}  		November 1976.  	 
\bibitem[Foster and Thomas ()]{b5}\label{b5} 	 		\textit{Managing Quality},  		 			S Foster 		,  		 			Thomas 		.  		2001. Upper Saddle River: Prentice Hall, Inc.  	 
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\end{document}
