The economics of a spinning process are essentially defined by three major cost blocks: capital costs and the interest burden on them, direct labor costs and energy costs. In order to compare economics, manufacturing costs are usually related to the production of 1 kg of yarn.
In rotor spinning, capital costs account for the majority of manufacturing costs (Fig. 99), followed by energy costs. Direct labor costs figure only in third place. This applies especially to countries with low labor costs. In countries with significantly higher wage levels, labor costs are higher than energy costs in the coarse count sector (but not in the fine count sector), due to the frequency of manual can and package transport movements (Fig. 98).
With the ring spinning system, direct labor costs in countries with higher wage levels account for a much greater proportion of the total and are almost identical to capital costs, followed by energy costs. This order changes accordingly in countries with low labor costs. Ongoing spare parts costs are a larger factor with rotor-spun yarn than with ringspun yarn, and space requirements account for a smaller proportion of total costs. Regional differences result in different weightings of the cost blocks.
The break-even point, up to which rotor-spun yarns can be produced more economically than ring-spun yarns, has moved continuously in the direction of fine count yarns in recent years – due to the increase in output. The output advantage of rotor-spun yarns is now so large that even the finest rotor-spun yarns (in the Ne 60/Ne 70 range) can be produced more economically than ring-spun yarns, and even in countries with low labor costs the cost of manufacturing rotor-spun yarns finer than Ne 40 is less than that for ring-spun yarns. Fig. 100 shows the manufacturing costs of ring-spun and rotor-spun yarns as a function of yarn count with differing regional labor cost levels.
The lower the share of the relatively high capital costs in manufacturing costs per kg of yarn, the more economically rotorspun yarn can be produced. The importance of capital costs declines if material throughput, i.e. the quantity of yarn produced per machine or spinning position, rises. Coarser yarns (with higher material throughput) can therefore be produced more economically than fine count yarns, both in absolute terms and also in comparison with ring-spun yarns.
The capital costs included the cost of purchasing the machine and all accessory equipment. Due to the high degree of automation and the ancillary equipment for quality control and waxing, a spinning position on a rotor spinning machine costs about 5 times as much as a spindle on a ring spinning machine. This is offset by the cost benefits of the rotor spinning system due to the elimination of sliver production, the possible saving of one drawframe passage and the elimination of the rewinding process.
If the capital costs and the production potential of the different spinning systems are compared, the situation given the current status of mechanical engineering is as follows:
- delivery speeds of the rotor spinning machine are a factor of 7 (fine yarns) to 10 (coarse yarns) higher than those of ring spinning machines;
- spinning-related ends down in rotor spinning are higher in proportion to spindle running times (per 1 000 spindle hours), but some 75% lower than those of ring-spun yarns in relation to a yarn length of 1 000 km;
- machine efficiencies of up to 99% are not unusual in well-managed rotor spinning installations; these figures are thus significantly higher than can be achieved with ring spinning machines.
To a limited extent, longer machines can help to reduce the specific capital employed per spinning position. Rotor spinning machines are currently being offered with up to 500 spinning positions. However, the useful limits are defined by reliably operating and economical drive technology.
Energy costs are becoming increasingly important worldwide. Limited resources mean that they are rising almost continuously. Their share of the cost of manufacturing a yarn is in many cases already on the same order of magnitude as labor costs. Close attention is therefore given to how much energy has to be expended to produce a given quantity of yarn. Machinery manufacturers make their contribution by working continuously and intensively to reduce the power input of the major consumers – i.e. the drives for the rotors and the fan for generating the partial spinning vacuum – as far as possible.
High rotor speeds can always be achieved when fine count yarns are being spun. In principle, the energy required on the rotor spinning machine increases with rising rotor speeds (Fig. 101). However, smaller rotors require less energy. For reasons of the mechanical stability of the rotors, higher rotor speeds can only be achieved with small rotors. Energy consumption with small rotors can therefore be entirely comparable with energy consumption using large rotors at much lower speeds. Yarn twist only has to be increased slightly with rising rotor speeds, since optimized spinning elements and improved spinning geometry contribute to improved spinning stability.
By contrast, the increase in energy consumption on the ring spinning machine is directly dependent on spindle speed. The diameter of the ring defines the weight of the cop and therefore cannot be exchanged like a rotor.
Rotor spinning offers especially high benefits compared to ring spinning as regards direct labor costs. High productivity, combined with the automation of the piecing and package changing process, means that the personnel effort required per kg of rotor-spun yarn is much lower than in ring spinning. Automated rotor spinning machines now require only minimal operator effort. Many more machines can now be allocated per employee, less and less personnel are required to operate a spinning mill. Automated solutions are available even for the remaining manual activities, such as replacing spinning cans, introducing the sliver into the spinning box and removing the full packages at the end of the machine (refer to section Machine and transport automation).