PROJECT 11:

YARN PROCESS ENGINEERING

11.1 Improving spinning Control plan database

Yarn process control planning is prepared firstly. All processes are listed. Then control plan for each one are prepared. And also for each control of process databases are made. System factors are taken into consideration during make database. At the result of this R&D project, databases are made for process and also following processes of the final product process. And also intelligent databases are designed through evaluating databases.

All these procedures are structured according to process and optimum quality/ minimum cost principles. After the project will be completed, all these procedures will be continued because of this working are extensive.

Table 5: Process Flow Scheme Of Knowledge Based Process Stages

 PROCESS FLOW SCHEME OF KNOWLEDGE BASED PROCESS STAGES

 1,1

 YARN DATAS

 TPC

 

 

 TEX

 

 

 PROCESS

 1,2

 YARN TYPE

 WEFT

 

 

 WARP

 

 

 KNITTING

 1,3

 MACHINE TYPE

 AIR JET

 

 

 RAPIER

 

 

 KNITTING

 1,4

 DESIRED YARN PERFORMANCE DATAS

 

 1,5

 DESIRED FABRIC PERFORMANCE DATAS

 

 

 

 

 2,1

 OPTIMUM BLEND SELECTION

 

2,2

 BLEND BALE MANAGEMENT

 

2,3

 BLEND TYPE PROCESS

 

 

 

 

3,1

 REAL YARN PERFORMANCE DATAS

 

3,2

 REAL FABRIC PERFORMANCE DATAS

 

 

 

 

4,1

 COMPARE BETWEEN 1.4 AND 3.1

 

4,2

 COMPARE BETWEEN 1.5 AND 3.2

 

 

 

 

5,1

 FIBRE CONTROL

 

5,2

 PROCESS CONTROL

 

5,3

 IMPROVING 2.3

 

 Optimum Quality Definition

As to Knowledge Based Quality Management System, Optimum Quality is to design raw material, semi-production, final production and process according to production quality criterions, which are according to System Factors, to be suitable for customer demands.

So basic of Optimum Quality is QFD system. QFD is not only adequate for determining Optimum Quality Criterions. It joins with Knowledge Based. Optimum Quality is designed to work with no problem and to contain no critic default in next processes of yarn (warp, sizing and weaving).

 Table 6: Determining Quality Criterions For Weaving Performance And Raw Fabric Quality

Determining Quality Criterions for Weaving Performance and Grey Fabric Quality

 

 

STD

OPT

QUALITY

CV%

 

 

 

INDEX

 

 

 

THIN/1KM

 

 

 

THICK/1KM

 

 

 

NEPS/1KM

 

 

 

RKM

 

 

 

RKM CV%

 

 

 

WORK

 

 

 

ELONGATION%

 

 

 

E CV%

 

 

 

KLASSIMAT (TOTAL)

 

 

 

HAIRINESS

 

 

 

PARAFFIN%

 

 

 

FRICTION COEFFICIENT

 

 

 

Breakage/1000-spindle hour

 

 

 

Warp breakage/1 million meter

 

 

 

Size breakage/loom

 

 

 

WST/100,000 weft

 

 

 

FST/100,100 weft

 

 

 

Default /100 meter

 

 

  1. Infrequent defaults don't form any problem on the quality of unbleached linen. So critic defaults are minimized.
  2. Secondly frequent default is thin, thick and neps.
  3. Continuously irregular is connected count %CV. And all stage of process must work regularly. So SPC must be established in the mill. Continuously irregular may be kept in security place but fabric view will have irregular.
  4. Especially fluffy is an important parameter for knitting, weft and also warp yarns.
  5. RKM and %CV of RKM that these two parameters depend on directly %CV change of fiber and fiber properties.
  6. %CV of yarn effects fabric view.

 All quality criterions must be suitable for customer demands. The value analyses for all these criterions are determined and translated to technical values by QFD systematically. At the result of this work quality improvement work becomes effectively.

 11.2 Fiber mix

 11.2.1  Select blends

Relations between with raw quality criterions and production quality criterions:

 11.2.2  Raw Material and Process

 11.2.3  Bale Management

 Blending mix are classified according to following yarn process data:

Blending mix are made according to measure bales weight or locals. Bales are labeled as to category system through result of measuring bales one by one. Category system guess depend on yarn resistance. In this way raw material cost minimized and provided to optimum quality.

 If Ne, TPI and Process Type are known, Fiber Class is presented to suitable for this. Cotton fibers are examined in 4 basic groups:

 Generally each class characteristics are different each other. Different properties of groups don't blend with another. It is possible to following mixture:

 But each bale is blended with same group for yarn and process quality.

 Working, which is related fiber control system in the blending, is:

  1. Prepare blending according to TPI, Ne and process. In this way production costs should be reduced to low level and at the same time quality defaults should be reduced.
  2. Minimize variation of yarn RKM through implementing category system.
  3. Determine especially %CV of fiber between bales and then improve mathematics correlation between CV% of bales and yarn quality criterions.
  4. Search thoroughly correlation between fiber properties and fibres cohesive forces and then examine to effect yarn these to friction coefficient.
  5. Classify scientifically cotton with category system and then get knowledge accumulation most extensive about limit of yarn spinning from these.

 11.3 Spin Plan

 The purpose of pc-program and R&D project is to provide to correct faulty process through check over draft Organization in the card, comber and their mixture. These processes begin from carding and continue to ring frame. Draft Organization has default; especially there is wavy view and long non-periodic default on the knitting fabrics. Thanks to implementing Spin-Plan, this R&D project are carried out in a short time. And it provides to increase production level from card to ring and also improving quality. Spin Plan presents %CV that must be according to desired yarn %CV on the carding, drafting and roving. As known well, in priority process from ring frame very low or very high %CV value effect negative to yarn quality. Spin Plan pc-program and R&D project get Poisson distribution infrequent defaults of yarn to lowest levels and give information which process damages yarn quality.

 11.4 Process Optimization Working with Technical Data/ Machine Settings

 Technical Data/ Mechanical Setting is important parameters to effects the costs. But it is important that which parameters are selected. For example: in the card, doffer turn is always calculated but no one calculates carding/cm. But carding/cm effects to form neps. So in this subject Technical Data/ Mechanical Settings working is an example for many mills.

 Technical Data/ Mechanical Setting is important for achieve quality and efficiently from blending to ring frame. Technical Data/ Mechanical Setting is databank to Spinning Mill DATABANK. The quality defaults are eliminated through determining all of technical data/ mechanical setting in the mill. Summary Technical Data/ Mechanical Setting;

 So Technical Data/ Mechanical Setting is changeable according to blending and yarn Ne. prepared pc-programs help to determine technical data/ machine settings. When Technical Data/ Mechanical Setting R&D project can be implemented, in the process stage and also ring frame,

 In the result of this working, yarn process parameters, optimum technical data/ mechanical settings, standard value and tolerances are determined. And then these data are database of Process Summary Pc-Programs.

 Technical Data/ Mechanical Settings and their standard values and tolerances are able to change physical characteristics of raw material. Faulty or unconscious settings cause fiber breakage, fiber abrasion and also to increase waste.

 Table 7: Relation with Technical Data/ Mechanical Settings and costs

Items Effected factors of increase costs

%Waste of blending

Technical Data/ Mechanical Setting, raw material properties, climate factors

%Waste of card

Technical Data/ Mechanical Setting, raw material properties, climate factors

Breakage

Technical Data/ Mechanical Setting, raw material properties, climate factors

Production levels

Technical Data/ Mechanical Setting, raw material properties, climate factors, training

Productivity (HOK)

Technical Data/ Mechanical Setting, raw material properties, climate factors, training

%Efficiently

Technical Data/ Mechanical Setting, raw material properties, climate factors, training

%Waste of comb

Technical Data/ Mechanical Setting, raw material properties, climate factors

Quality defaults

Technical Data/ Mechanical Setting, raw material properties, climate factors, training

 Pc-programs include to technique computes of machines, machine data, technical data/ mechanical settings, optimum changeable compute of cylinder and gear and kinetic charts. While implementing pc-programs, quality correction working and training are done.

 We benefit from spectrogram and diagram analysis. Spectrogram is a line diagram, which shows diameter of unit length or weight change through Fourier series. Mechanical default joins extra line on the spectrogram line. Diagram shows weight or diameter changes and also in the diagram default is founded. A spectrogram curve or line gives,

In the fibrogram drafting default is determined through compare with spectrogram curves.

Computing mechanical default takes long time by spectrogram. But by help of computer, it takes short time and also prior and next processes are controlled better. Mechanical defaults, which become in either card or draft, cause thick and thin places and increase breakage in weaving. Therefore mechanical defaults must be eliminated.

 Spectrogram programs are basic of "spinning mill databank". Each machine must have in the mill,

 All machine in the mill are taken in control. While implementing these programs, all test machines are used efficiently. Effects of machine settings changes on yarn quality are taken in control. All these workings provide,

 Knowledge Based Quality Systems             Proses Optimization and R&D Projects for Textile Mills