In a world of changing demands and financial recession, the garment manufacturing is increasingly facing lower margins. Combine this with buyers’ reducing stock levels, faster and more reliable deliveries, higher quality-standards at better price points, harder to process fabrics. Machinery is becoming more technically complicated to maintain and manage; operators want more wages, and managers appear to be sinking with the business results. All these conditions and more, are forcing manufacturing businesses to become much more professional world wide (low wages definitely are becoming a short-term substitute) and businesses need to face the challenges and in reality challenge is controlling time and money in the manufacturing process to be profitable. In the first of the two article series, John Irvine a veteran of 30 years in managing, consulting and mentoring the industry, analyses the critical factors responsible for lost time in apparel manufacturing.
It is extremely important to control manufacturing parameters which influences time, which one may think is old soap but the basic parameters require to be addressed before a business can build a good foundation and have a strong flexible framework to encourage and develop modern techniques. The idea is to analyze what can be done by viewing where we are at present and seeing where more effort requires to be imposed. Egotistical or those who are content with their achievements will find reasons not to follow the process, but for the professionals who know they must improve without any compromises.
Standard data gleaned from a variety of sources were applied and averaged from factories who record such detail for payment. It becomes apparent that this type of knowledge identifies problems requiring solutions to precipitate business profits and operators earning capacity. The parameter elements used as set out are shown in Table 1.
It is a known fact that 90% on-standard operation performance reduces further due to several off-standard elements. Table 2 illustrates how 400 minutes available or worked minutes with no off-standard elements to a ‘90% on-standard’ operator is reduced due to 12% ‘absence’ in a factory which is just one of the many off-standards. This reduces the worked minutes to 352.
Although any one operator may not be absent, but to mathematically build averages, all the off-standard elements are applied to any one operator. So, the worked minutes are 400 and when applying absence this figure drops to give 352 available work minutes and since the operator is ‘90% on-standard’, actual minutes produced by the operator is just 317 minutes. Thus, the actual utilization of the worker is 79% (317X100/400). On the top of this if the quality problem results 16% off-standard time, then there will be further reduction in worked minutes to 296, minutes produced to 266, utilization to 67%. Similarly cumulative reduction of time after all off-standard data will result in effective time produced to only 203 minutes, which is only 51% utilization!
It is a common knowledge that higher the utilization percentages of a line or factory, better is its performance. It is a common but important measure in sewing floor. Let’s take a factory of 700 operators working over 2 shifts, 350 operators each shift working 400 minutes per day 6 days per week.
Available minutes for 700 operators per day are 700X400 = 2,80,000 minutes per day. 6% overtime means 16,800 minutes; this is averaged into each individual operator for calculation, which is equivalent to 140 operators working 2 hours per day and 3% is equivalent to 70 operators working for 2 hours per day. Absenteeism in current state is 12%; if the desired target is 6% then potential for time saving per day is 24 minutes (6% of 400 minutes). Similarly, time spent on bad quality is currently 16%, if we set a target of 4% (i.e., 12% reduction), then potential for time saving per day is further 48 minutes (12% of 400 minutes). Thus, if we aim to reduce all the off-standard elements by above mentioned amounts then total cumulative time saving potential is 158 minutes.
Measuring Utilization
As observed in Graph 1, the decline of utilization percentage varied from 10 to 18%, when only one off-standard element ‘quality’ was considered in isolation. But when combined with other off-standard element like absenteeism reduced the percentage utilization by 16% (at 60% on-standard performance) to 29% (at 110% on-standard performance – Graph 2).
Whereas, when the ‘utilization’ is drawn against a base of ‘on-standard’ efficiency (The base is condition when there are no off-standard elements) and measure the difference in the application of decreasing off-standard from “current results” to “desired results” as outlined in Table 1, it becomes clear how utilization percentage change when all the off-standard elements are applied cumulatively or those off-standards working simultaneously in a factory.
Each line in the graph represents the decrease in utilization percentage when each off-standard element is applied one by one upon the previous one. For example, Absenteeism reduces the utilization by a maximum percentage varying from 7% (at 60% On-standard performance) to 13% (at 110% on-standard performance). Quality, another ‘off-standard’ further reduces utilization by 9% (at 60% on-standard performance) to 16% (at 110% on-standard performance).
The base utilization in this case represents worker utilization when no off-standard elements are existing, which means when no time is wasted due to bad quality, machine breakdown, waiting for pieces, absenteeism, poor line balance, etc. it is evident from the Graph 2 that a large chunk of utilization can be realized by fixing every off-standard element.
It can also be concluded from the same graph that lines representing ‘overtime’ and ‘line imbalance’ is almost coinciding. This illustrates that when all off-standard factors are present in a line/factory, working overtime has very little improvement in utilization percentage.
The most profitable element is getting quality correct, which will automatically give machine off-standard gains (the difference between the base graph and the quality graph is visibly large denoting large reduction in utilization percentage). It is definitely worth the effort to quality correct off-standard.
Operator performance is purely a repeatability of method. The ability to organize and control the labour resource, the better is the utilization percentage. If we look at the graph above and follow the base line and match for 80% on-standard performance, we will find that the utilization percentage is 80%. If we look up on the same on-standard performance during absenteeism and machine breakdown, we will clearly observe that the utilization percentage is now nearly half way down to 44% minimum and 81% maximum.
This means that a business that has the operators performing at 80% on-standard realizes without the control of off-standard times a 44% utilization, whereas with control it can perform at a 80% utilization, a gain of 36%. All that has happened is the operators have not been working for all this time. They are either waiting for their machines to be fixed or are reworking on the defective pieces.
It is a common knowledge that higher the utilization percentages of a line or factory, better is its performance. It is a common but important measure in sewing floor
There are several companies which have accepted a lower utilization percentage and have attributed it to style changeovers. But as my experience and the graphs suggest it is the total lack of management control as more than 60% of the operations are similar among the styles. This could relate to a number of things such as poor planning (putting styles on lines that need total re-training), machine setup, poor quality and last but not the least poor risk analysis of the style. Absence is normally a sign that operators do not want to work due to adverse conditions such as waiting, poor machines, being shouted at, no encouragement, lack of leadership and poor wages or even round pegs in square holes, poor job selection.
Increasing Standard Minutes
It can be easily seen that utilizations of 70 to 80% and above are achievable. All it takes is determination of team building and finding the root cause and solving it permanently. I understand it is not a systems problem and because it has been achieved in different countries it is not a country cultural problem either, but simply a management problem. I have personally witnessed and achieved this type of result in many places. The operators are receptive when they realize they are being helped and not scolded
It is often said that high performance reflects the repeatability of method, and in most factories that I have experienced, few seem to understand the principle of method, or perhaps do want to understand it for whatever reason. Method should be very detailed and not a gloss over job as I have seen in many factories where method is everything for costing purposes but in reality a piece of paper for production purposes. The production manager sets the methods. Seems a bit illogical when one considers that the business needs to beat the standard minutes set for price point and delivery. If the production managers can beat the time allowed it’s good… I suggest they are in the wrong job and vice versa.
Operators can perform above a 100% through two ways. The first, those workers who are exceptionally skilled and who can do actions that others cannot do, that is they are termed super skilled operators and not always easy to recognize. The second, is the normal way by not using the allowances built into the piecework rate. Allowed in most piecework rates is 15% allowance (i.e., 60 minutes; 15% of 400 minutes) on the 100% value which usually accounts for lost time due to interferences such as thread breaks and fatigue. However, many businesses have evolved from that and the only real lost time is toilet and thread changes. This in reality amounts to 12 minutes in a shift so the operator works for a further 48 minutes (60–12 minutes) per day. At 100 performance represents 448 minutes (400 + 48 minutes) produced divided by 400 attended minutes, a 116% performance level. The allowance is now a further incentive pay for effectiveness and effort of repeatability. I have found in practice that this reflects in the attitude of the operators working in a team rather than as individuals. Let us also consider-standard minutes produced against on-standard performance for 700 operators working in a factory.
The graphs (Graphs 3 and 4) here refer to on-standard performance and generated standard minutes, a straight line relationship. Graph 3 with individual off-standard element (quality) again indicates that best gains present themselves when quality is controlled. In other words, if not controlled, the quality off-standards could prove very costly for the company leading to a massive reduction in standard minutes (26,000 – 50,000 minutes everyday).
But when coupled with other off-standard elements (Graph 4), the cumulative effects can be disastrous with more than half of the available standard minutes being lost. The Graph 4 shows the losses from the “base value” to the “current value” of available standard minutes. As the graph on utilization serves to indicate that controlling off-standard time has a lot of value and performance is not the only element of greater production.
On close scrutiny we will notice that overtime is not so successful in increasing produced standard minutes. It just increases them by a minor value of 5000 – 10000 minutes for 700 workers (per worker increase of 8 – 14 minutes), for which the factory has to pay. This increase in standard minutes just compensates for the off-standard balance. Thus, we realize that instead of paying overtime, if we could just balance the line properly, we could get much more standard minutes everyday than by paying overtime to unbalanced lines.
All the information presented assumes that overtime worked produces standard minutes and is not worked for repairing garments for any reason. When I first came to India, it was the first time I had seen paid overtime being worked to repair garments as a matter of course. After further investigation a lot of the overtime was worked because the production manager had failed and it covered the weaknesses in production without highlighting the major problems. They had not been professionally trained to understand the concepts of their actions.
Conclusion
It can be easily seen that utilizations of 70 to 80% and above are achievable. All it takes is determination of team building, finding the root cause and solving permanently. However, having achieved results like this in Morocco, Romania, UK, China and Moldova, I understand it is not a systems problem and because it has been achieved in different countries it is not a country cultural problem either, but simply a management problem.
I have personally witnessed and achieved this type of result in many places. The operators are receptive when they realize they are being helped and not scolded. They were not working any harder or faster but were trained to be more effective with their time through correct training.
This training was done through personal attention and training and sometimes through using video training. The difference reflects an attitude, and not a cultural change. The best thing about it is that it did become a cultural change, a factory cultural change.
Industrial engineers are not always trained to do their job but more surprisingly nor are the trainers nor the production managers who train to different methods and ultimately the business is limited by their knowledge and the effect on standard performance.
My first suggestion is to record such data through a wage scheme and time clocking which gives accurate data and historical data to control badly managed time elements. Yes, costs may rise slightly but the financial gains of having the finger on the real issues outweigh that small cost to make real profits as will be shown. The second suggestion is to train managers and engineers in method application. The third and final suggestion is to follow the method vehemently from start to finish.
