The advent of stone-age instilled indefatigable habit to invent precision tools and machineries, to enhance productivity and to add comfort to life at work place. Garment was no aberration, it moved from hand stitching to paddle-run machines and now finally graduating to various specialized machines, running on electric motors supporting multi operations and automation. In fact the machines are designed to cater to specific task with flawless quality and with minimal human interference.
Constantly rising cost of labour encouraged the users to check out machine inventory periodically, update it and explore the necessity of changing or substituting it for better productivity and profits without additional liability, reveals Pradeep Jha, a garment technologist with experience in a Sri Lankan company SKD-Pacific as Production Executive, Head of R&D at Instyle Exports and now offering his services as a Consultant to the industry.
After 20 good years of uninterrupted growth in the apparel export industry, the parameters started changing and as late as 90’s buyers became more demanding, asking for better product quality. They also became highly conscious about working only with the socially, environmentally and technically compliant factories. Sensitivity of buyers towards child/bonded/underpaid labour forced exporters to stop subcontracting from unorganized, small and unregulated manufacturing units. All this resulted in opening of company-controlled manufacturing units, but for an industry used to outsourcing through unorganized units, to run factories in a more organized manner and in a socially compliant environment resulted into escalation of manufacturing cost. This escalation started eroding profit margins as prevailing market conditions were not supporting increase in FOB prices.
| Some of the features that influenced the export | |
| Unfavourable | Favourable |
| Focus on quality | Machines more accurate and cheaper |
| Pressure on costing | Better information and production technology |
| Competition taking global nature | Distinction for performer |
| Global downturn | Surge in domestic demand |
| Raw material more expensive | Local sourcing destination |
| Labour more expensive | Availability of trained professionals |
With the steady rise in the cost of labour, stringent quality and tighter costing, led to the inability of the factories to feed the large work force and extract quality-efficient output in the required time period, which led to the consolidation or closure of several units. On the other hand organizations which were able to plan well and get quality output at higher efficiency were rewarded with healthy growth and good returns.
The art of running a garment production is now no longer a poor man’s job. It requires the skills and professional understanding to manage man, machine and money, the traditions being replaced with scientific innovations.
[bleft]Employees are always an escalating cost factor for the organization, but machines are one-time investment which becomes less expensive with usage. Older the operator higher will be his wages but lower will be his output due to ageing[/bleft]
Quality Production
Machines rarely deviate from stated or implied quality standards if it is fixed and maintained properly, whereas quality of output especially in the garment production which is more or less dependant on the humans succumbs to his mood, sincerity, ability to understand and judge, prevailing climate, and many such factors. Production system, which uses limited manpower, that too as an extension of machines following few instructions, are often characterized by high productivity and efficiency. Role of human should only be confined to operate and instruct machines; right to work should be the total prerogative of machines. We can be assured of stated quality output when handling machines properly. Further specialized machines restrict work from going into many hands, which in turn drastically reduces probability of occurrence of defect. Elimination of operation/s yields into reduction of a station/s from quality radar, where deviation could have taken place.
Quality output from scientific against traditional approach, we will try to analyze through an example assuming buyer’s required quality level are AQL 2.5. Only two operations of a ladies blouse have been considered to keep it simple. As we progress with calculation table, we will discover that each operation if done traditionally has the potential to get the whole lot of garment rejected, since they are handled many times.
Example-1: Operation: marking for dart on front panel.
Case A – using machines = one time [put a drill mark on front cake ® put notches for dart ends]
Case B – manually = 70 times [take a front panel ® put marking template on it ® mark for dart ® remove marking template ® pair or arrange panels]
Example-2: Operation: Making of imitation placket (cut and sew).
Case A – using DNCS with folder = stitch placket in one stoke (one operation).
Case B – using SNLS = crease placket ® attach placket to body ® close placket ® put stitch on other placket end (4 operations).
Faster Pace with Higher Productivity and Better Efficiency
Machines predominantly minimize work content of operations by either eliminating or clubbing a few operations, else by reducing handling time required to accomplish operations. Machines are designed for a specific task and give a consistent output tirelessly.
| Data Table: 1 Comparing Operation done mechanical against manual method | ||||
| Total operations | Probable quality deviation points | Standard defect % = 1% * | Expected no. of defects. | |
| Example-1 | ||||
| Case A | 1 x 2 | 2 | 2 x .01 | 0.02 |
| Case B | 70 x 5 | 350 | 350 x .01 | 3.5 |
| Example-2 | ||||
| Case A | 70 x 1 | 70 | 70 x .01 | 0.7 |
| Case B | 70 x 4 | 280 | 280 x .01 | 2.8 |
It can be seen from Data Table: 1 that operations were drastically reduced when done mechanically in comparison to corresponding manual methods. Needless to elaborate that when it is executed by a machine, we require much less man-hour. In less man-hour we get more production hence our productivity increases. Higher productivity often supports fewer man-power, besides better utilization of man-power, better balancing of operations in a batch, lower WIP and lower lead time (Lower lead time also assist in catching deviation and correction much earlier).
Let us study the discussed parameters through two operation bulletins of same style for same targeted output (data table 2 & 3).
Style: Ladies blouse with imitation placket, double pocket, double stitch on pockets, collar, shoulder seam and armhole seam.
Less number of operations has not only reduced head count but has also contributed in reducing the number of machines required to extract same production. Less number of operations helps in organizing production process and gives sharper control to ensure better quality yield.
Reduced Operational Cost
Specialized machines reduce cost by enhancing productivity, confining operation to less number of machines and accomplishing same task with less number of people, whereas semi-utilized/idle or over-staffed factories are characteristics of a morbid organization. Employees are always an escalating cost factor for the organization, but machines are one-time investment which become less expensive with usage. Longer the machines are used lesser the liability it will be to the organization albeit with same output. Older the operator higher will be his wages but lower will be his output due to ageing. Production in garment manufacturing factories fluctuate month wise since orders are inconsistent and are dictated by prediction by marketing, actual selling and market response to produced styles. The capacity of a unit is planned keeping peak production demand in mind, which implies that factory will be fully utilized only at the time of peak production and rest of the year it will remain underutilized. Normally a calendar year of garment factory in north India can be summarized in the Data Table 4 in terms of capacity utilization.
| Data Table 4 : Capacity utilization of a typical North Indian factory | ||||
| Production | 100% | 80% | 60% | 40% |
| Duration | 5 months | 2 months | 4 months | 1 month |
| Loss of production in a year | 21.67% | |||
Idle machine will warrant only periodical maintenance but the idle manpower will demand full payment with basic facilities like transport, light, and support staff. Data Table 5 gives expenses incurred on wages, distributed for idle time in one calendar year corresponding to the size of unit. If we improve our efficiency by 22%, we can save big money otherwise this money is spent as wages paid during non productive time. Attaining better efficiency may be reality only with procurement of some specialized machines operated by motivated and trained operators. This should not be a daunting task since one factory with 100 machines can facilitate buying of 152 machines by improving efficiency by 22% [find details in Table 5 below]. To improve efficiency we will never require 152% additional machines, to the maximum we may need to replace 25% of the existing machines. By replacing with superior machines, reorganizing production processes, proactive production planning it should not be difficult to enhance efficiency by 22%, when most of the factories in Delhi are working at efficiency level of 40% to 50%. Efficiency may follow superior machines, saving may follow efficiency and not otherwise in either cases. Updating machine and method should be integral part of progressive organization.
Another way of looking into it is, if there is a small increase in productivity, it will result into substantial increase in profitability and turnover of the organization as reflected in Data Table 6. (Monitor that more people are not recruited to support more production per machine; since more workers will dissolve efficiency percentage).
To buy a machine you need to have only rational business thinking but to employ a person you must take a very guarded call, since wage of one employee has potential to eat profit generated from one machine (man to sewing machine ratio is 1:2.5 in garment units which ideally should be1:2.5). This signifies that profit generated from hard work of 2.5 people, may be negated by recruitment of one extra person in the organization.
| Data Table 5 : Expenses incurred on wages distributed for idle time in one calander year | ||||||
| M/c in the Factory | Expense/Month | Expense/Year capacity | Loss due to unused | Wages paid during non productive time | ||
| 100 | 1750000 | 21000000 | 4550700 | 2912448Is depreciation & interest of152 m/c | ||
| 125 | 2187500 | 26250000 | 5688375 | 3640560Is depreciation & interest of190 m/c | ||
| 150 | 2625000 | 31500000 | 6826050 | 4368672Is depreciation & interest of228 m/c | ||
| 175 | 3062500 | 36750000 | 7963725 | 5096784Is depreciation & interest of265 m/c | ||
| 200 | 3500000 | 42000000 | 9101400 | 5824896Is depreciation & interest of303 m/c | ||
| 225 | 3937500 | 47250000 | 10239075 | 6553008Is depreciation & interest of341 m/c | ||
| 250 | 4375000 | 52500000 | 11376750 | 7281120Is depreciation & interest of379 m/c | ||
| 275 | 4812500 | 57750000 | 12514425 | 8009232Is depreciation & interest of417 m/c | ||
| 300 | 5250000 | 63000000 | 13652100 | 8737344Is depreciation & interest of455 m/c | ||
Understanding row-1,
- Factory consists of 100 machine, expense incurred per month = No. of machines X expense incurred per machine / day X no. of working days in a month = 100 x 700 x 25 = Rs.1750000. [assumption – Rs. 700 is incurred to run a machine (includes all direct and indirect expenses of unit)].
- Expense/year = Expense/month X no. of month in a year = 1750000 x 12 = Rs. 21000000.
- Loss [money] due to unused capacity = Expense/year X production loss% [ref. Data Table: 4 = 21.67% = Rs. 21000000 x .2167 = Rs. 4550700.
- Wages paid during non-productive time = Rs. 4550700 X .64 [share of wages and salary in total expense is approximately 64%] = Rs.2912428.
- Rs. 2912448 [Wages paid during non productive time] is depreciation & interest of 152 machines based on below assumptions.
- Average price of productive machines is Rs. 60,000.
- Rate of depreciation is 20%.
- Rate of interest for machines is 12% per year.
| Data Table 6 : increasing profits with productivity | ||||
| Productivity per m/c | Yearly prod/m-c | Avg fob in Rs. | T/O per m/c Cr. | Profit share in Lacs |
| 7 | 2100 | 240 | 0.05 | 1.01 |
| 8 | 2400 | 240 | 0.0576 | 1.152 |
| 9 | 2700 | 240 | 0.06 | 1.3 |
| 10 | 3000 | 240 | 0.072 | 1.44 |
| 11 | 3300 | 240 | 0.08 | 1.58 |
| 12 | 3600 | 240 | 0.0864 | 1.728 |
| 13 | 3900 | 240 | 0.09 | 1.87 |
| 14 | 4200 | 240 | 0.1008 | 2.016 |
| 15 | 4500 | 240 | 0.11 | 2.16 |
| 16 | 4800 | 240 | 0.1152 | 2.304 |
| 17 | 5100 | 240 | 0.12 | 2.45 |
- If factory is delivering productivity of 7 garments per machine, then on machine will produce 2100 garments in a year [7 garments in a day X 25 working days in a month X 12 months in a year].
- It is assumed that garments are offered to buyer at $ 5 = Rs. 5 x 48 = Rs.240 = average fob.
- Turn-over per machine = No. of garments produced in a year X average FOB = 2100 x 240 = Rs.0.05 crore.
- It is assumed that factory is working with 20% profit margin, hence profit generated per machine = Rs. 0.05 crore x 0.20 = Rs.1.01 Lakh.
- With increase in productivity we see profit share, i.e. profit generated by each machine increases substantially.
