What is Bale Management?
Bale management refers to the process of inventory control and selection of fiber according to its properties and also to mix fiber homogeneously to get acceptable spinning performance, consistent production and quality of yarn. The function of bale management is very much unique to the spinning industry. The module should have a function in such a way that the system should automatically generate the issues for mix or a count, where all the lay down or issues should have a consistent quality parameter both in terms of average and SD.
So, we can define bale management in the following way: Testing, sorting and mixing bales according to the properties of fibers for producing specific good quality of yarn at minimum cost is called Bale management. Bale management is the important step of cotton fiber engineering and in dealing with storage and retrieval of cotton bales.
Various definitions are given for bale management. Among them popularly used are as follows:
Bale management is a sophisticated attempt to acquire the raw-material with desired characteristics to parameters categorized and store bales according to predetermined patterns and to select and blend bales in order to attain a consistent and uniform product.
Bale management is a process to mix fiber homogeneously to get consistent production, quality of yarn, inventory control and selection of fibers according to its properties.
According to the fiber characteristics:
Bale management refers to a choice of cotton bales in order to achieve acceptable and a constant yarn quality and economical processing conditions.
Objectives of Bale Management:
- An evening out of the quality characteristics of a yarn.
- A means of avoiding quality jumps.
- A possibility of reducing costs as a result of an improved knowledge of the fiber characteristics.
- Origin: CIS (Uzbekistan) raw cotton
- Crop year: 2008-2009
- Bale weight: 215-220 kgs (approximately).
- Staple length: 1 inches
- Micronaire: 4.0 – 4.8
- Strength: 24-29 gram/tex
- Grade: SMW (Strict middling white)
- Price: 65.5 usc/lb
To manage the bales we need four modules of fibers and the relation exist between fibers and yarn. They are:
- Color grade and
- Micronaire value
Procedure of Bale Management in Spinning Mill:
Raw material selection (fiber lot number)
HVI (High Volume Instrument) testing
Number of mixing
Category defines (micronaire value and color grade) for different mixing
Discard the lower micronaire value and color grade bales
Define daily requirements
Receiving and ware house punning
Evaluation by QA personnel
Preparation of bale layout as per mixing
Delete the consumed bale from the current bale
Factors for Effective Bale Management:
- If the cotton received is from different ginners, it is better to maintain the percentage of cotton from different ginners throughout the lot, even though the type of cotton is same.
- It is not advisable to mix the yarn made of out of two different shipments of same cotton. For example, the first shipment of Sudan cotton is in January and the second shipment is in March, it is not advisable to mix the yarn made out of these two different shipments. If there is no shade variation after dyeing, then it can be mixed.
- Stack mixing is the best way of doing the mixing compared to using automatic bale openers that picks up the material from 40 to 70 bales depending on the length of the machine and bale size, provided stack mixing is done perfectly.
- Improper stack mixing will lead to barre problem. Stack mixing with bale opener takes care of short-term blending and two mixers in series takes care of long-term blending.
- Tuft sizes can be as low as 10 g and it is the best way of opening the material (nep creation will be less, care has to be taken to reduce recycling in the inclined lattice).
- The raw material gets acclimatized to the required temperature and R.H% since it is allowed to stay in the room for more than 24 h, and if the fiber is opened, the fiber gets conditioned well.
- Process Management in Spinning by R. Senthil Kumar
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- Engineering Cotton Yarns with Artificial Neural Networking (ANN) By Tasnim N. Shaikh and Sweety A. Agrawal
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Founder & Editor of Textile Learner. He is a Textile Consultant, Blogger & Entrepreneur. He is working as a textile consultant in several local and international companies. He is also a contributor of Wikipedia.