Gone are the days when quality of the product was solely dependent on the strong and mighty quality control department. Regular policing to find defects and deviations, identify corrective methods to repair defects and reinstate them into the product batch was the standard state of affairs. The department boasted of an army of quality controllers and assurance staff at various levels and included clustering of a number of unproductive reports, but still couldn’t vouch for meeting the acceptable quality level when the shipment was offered for customer’s inspection. The apparel industry today is no different as far as the evolution of quality assurance techniques is concerned. In the past two decades, the industry has scaled through many phases of quality management systems and standards together with more effective data collection methods and reporting systems. The objective is to meet customer satisfaction by virtue of the systems implemented in the organization. Thanks to these initiatives, the general perspective on product quality and the means to achieve the same has been changed drastically at manufacturer’s end. Jayapal Nair, Apparel Manufacturing Expert, Consultant and Author, takes a look at efficiency beyond ’80s model in apparel manufacturing…
The recent evolution in apparel quality management has come from the emergence of Quality Engineering (QE) concepts – mostly associated with the software industry – which are slowly trickling down into the industry and gaining momentum as well. The QE principles have to be tailor-suited and simplified for the garment industry to drive its quality objectives. In this concept, the quality is in-built in the entire process of manufacturing, starting from the handling of raw materials to the finished goods. The requirements of engineering the processes and making the ‘right quality propelled decision’ are based on two key functions: Risk Identification and Predictive Quality Analytic Techniques.
The right QE system adds tremendous value to the product quality and reduces cost by eliminating worthless checkpoints.
Methodology
Similar to an industrial engineer who prepares an operation bulletin which is the script for executing efficient production, the quality engineer does the QE bulletin in a wider perspective to infuse product quality during processes. Just when the orders are allocated to a supplier, even before the raw material is brought into the factory, the quality engineer has to identify various risks involved with the order. The risks, including its grade, based on probability and severity are evaluated under the below categories (similar to risk analysis in safety standards) considering certain specific elements:
a) Style related – The elements of evaluations are: Order quantity, number of SKU’s involved and criticalities of style construction.
b) Material related – The elements considered are the physical properties of fabric and trims.
c) Manpower related – The elements considered are worker’s expertise and factory’s (or the specific assembly lines’) past performance in terms of quality.
d) Machinery/Equipment-related – Deals with the suitability of machinery/tools (e.g.: machine gauges, needles, etc.) available at the manufacturing factory.
e) Process related – Deals with the risk elements during each stage of manufacturing: cutting, printing, embroidery, fixing of appliqués, sewing, washing, finishing, etc.
f) Management-related – Deals with the attitude and skills of management staff and even considers availability of a resourceful manager during the style run period.
Table 1: An example for Risk Assessment Report is given below:
| Consider a man’s pant style with elasticated constructed waistband/double fly/2 back welt pocket/blind hem with an SMV of 34 minutes. There are 24 SKUs | ||||||||
| (waist x inseam combination). Based on a detailed Risk Assessment Report, the organization can make a learnt decision to select the factory/assembly line on which the specific style can be put into production. This will help in drastically reducing the quality and production issues during processes. | ||||||||
| Factory Name: xxxxx Assembly Line No.: yy | Prepared By: QE | Risk Mitigation Strategy | ||||||
| Serial No. | Category related to | Elements for evaluation | Data available |
* Risk level benchmarks: High = 1, Medium = 2, Low = 3 |
** Potential risk level: High = 1, Medium= 2, Low = 3 | Action Plan | Responsibility | *** Time Schedule |
| 1 | Style | Order Quantity | 5,000 pcs. | <10,000 pcs. is considered high, 10,000-20,000 is medium, and >20,000 is low | 3 | See the possibility to combine similar styles | IE/ Merchandiser/ Planner | 20 days before cutting |
| No. of SKUs involved | 24 | >= 15 is high-, 9-14 is medium, <8 is low level risk | 3 | Displays to be provided to the operations where SKU-related trims are used e.g.: zip attachment, label attachment | QE | 2 days before style is planned for cutting | ||
| Criticalities of style construction | Elasticated waistband, welt pocket, bottom hem (there can be many) | Risk can be of low-, medium- or high-level based on the line’s experience | 2 | Pre-training for workers must be planned; mock displays to be provided | IE/QE | 10 days before sewing process starts | ||
| 2 | Material | Properties of fabric | Polyester rayo | Risk can be of low-, medium-, or high-level based on the factory’s warehouse facility | 2 | Ensure proper stacking, grouping, covering, etc. Consider experience from sewing assembly lines to handle this specific fabrication | Fabric Manager, QE | On the date when fabric is in-house |
| Properties of trims | Un-shrunken elastic | Risk can be of low-, medium-, or high-level based on the factory’s facilities | 3 | Ensure elastic is shrunken for a planned duration. Divide between shrunken and non-shrunken elastic. Must be issued to sewing without any mix-up | Store Manager | On the date when trims are in-house | ||
| 3 | Manpower | Workers’ skill | Availability of specific skilled operators | Risk can be of low-, medium-, or high-level based on the availability | 2 | Allocate as per skill matrix | IE | 1 week before sewing process starts |
| Quality efficiency | <80% in last 3 months | <80 is high, 81-90 is medium, and >91 is low-level | 1 | Audit points to be identified on the basis of quality performance | QE | 1 week before sewing process starts | ||
| 4 | Machinery & Equipment | Suitability of machinery | Auto pocket welt machine is not available | Risk can be of low-, medium-, or high-level based on availability | 1 | Check if machine can be arranged for or begin training an operator for manual process for welt making | Maintenance Manager, Technical Manager/IE | 1 week before sewing process starts |
| Suitability of equipment | Machine gauge set is not available for WB preparation | Risk can be of low, medium, high-level based on the availability | 1 | Arrange for the required gauge set | Maintenance Manager | 1 week before sewing process starts | ||
| 5 | Process | Cutting | Lay height | Number of plies decided corresponds to the risk | 2 | Prepare a cut-plan considering the number of plies allowed | Cutting Manager | 1 week before cutting process starts |
| Printing | Not applicable for this style | |||||||
| Embroidery | Not applicable for this style | |||||||
| Fixing of appliques | Not applicable for this style | |||||||
| Sewing | Identify all critical operations | Risk level of operations to be decided on criticality basis | Waistband attachment risk level = 1, Welt making process risk level = 2 | Make risk elimination plans against each critical operations | QE/PM | 1 week before cutting process starts | ||
| Washing | Not applicable for this style | |||||||
| Finishing | Garments to be shifted to hangers in order to avoid crushing | Risk based on availability of hanger stand, finishing room layout, etc. | 2 | Layout needs to be arranged in order to accommodate hanger stands | IE/GM | 1 week before cutting process starts | ||
| 6 | Management | Attitude and skill | Excellent | Average-high risk level, good-medium risk level, excellent-low risk level | 3 | GM | 3 days before style is being planned for cutting process | |
| Availability of resourceful management | Technical staff is available during style run | Average-high risk level, good-medium risk level, excellent-low risk level | 1 | Assign a good technician to this assembly line, while production for selected style runs | GM | 3 days before style is being planned for cutting process | ||
| # Data available column to be prepared in detail (mentioned only a few in this chart). * Risk benchmarks can be set by the factory based on their status on various category. ** Potential risk level to be identified based on actual data against benchmarks (figures given in the chart are the examples). *** Time schedule can be set by factory considering their own process turn over time and feasibilities. |
||||||||
After identifying all these risk factors, risk mitigation is to be formulated which includes the action plan, the person responsible and time schedule. The effectiveness of implementation can be ascertained by conducting sample audits and calculating individual “quality efficiency”.
Quality Efficiency = (No. of audits passed) x 100
(No. of audits performed)
A proper risk assessment report will help in taking right decisions while planning and allocating resources, rather than an impromptu decision.
Table 2: Examples for Predictive Quality Analytic Report:
| Serial Number | Activity | Stage of Occurrence | * Operation | ** Potential Problems | Origin of Problem | Technique Employed for Problem Solving | Stage of Control | Person Responsible | Checking Method | Frequency of Checks |
| 1 | Cutting | Laying | Laying | Uneven ply-width in completely spread lay | Plies are not aligned by the spreader at one edge | Check the clip positioning where one edge of lay is aligned. Also, check the skill level and training undertaken by spreader | During lay table preparation | Cutting Manager/ Supervisor |
Check the positioning by using a calibrated steel scale | Audit by Cutting QA |
| Cutting | ….. | ….. | ….. | ….. | ….. | ….. | ….. | ….. | ||
| Numbering | ….. | ….. | ….. | ….. | ….. | ….. | ….. | ….. | ||
| Fusing | ….. | ….. | ….. | ….. | ….. | ….. | ….. | ….. | ||
| Bundling | ….. | ….. | ….. | ….. | ….. | ….. | ….. | ….. | ||
| 2 | Sewing | Parts 1 | Joining of waistband to garment body | Uneven structure after joining | Segments are positioned unevenly | Fix a T-guide with machine | Waistband joining operation | Team responsible for line setting | Check by placing piece on top of hard-pattern after joining | Audit by Roving QA |
| Parts 2 | ….. | ….. | ….. | ….. | ….. | ….. | ….. | ….. | ||
| Back | ….. | ….. | ….. | ….. | ….. | ….. | ….. | ….. | ||
| Front | ….. | ….. | ….. | ….. | ….. | ….. | ….. | ….. | ||
| Assembly | ….. | ….. | ….. | ….. | ….. | ….. | ….. | ….. | ||
| 3 | Finishing | Thread trimming | Thread trimming | Blind hem unravels | Thread was trimmed too close to the garment body | Lock end threads and trim with the ¼ inch thread trail. Also, train operator | Thread trimming | Trimmer (Trimming Operator) | Visual Inspection | Audit by Section QC |
| Checking | ….. | ….. | ….. | ….. | ….. | ….. | ….. | ….. | ||
| Ironing | ….. | ….. | ….. | ….. | ….. | ….. | ….. | ….. | ||
| Tag fixing | ….. | ….. | ….. | ….. | ….. | ….. | ….. | ….. | ||
| Folding | ….. | ….. | ….. | ….. | ….. | ….. | ….. | ….. | ||
| * Under the column ‘operation’, all operations from the IE bulletin can be inserted so that no operations will be missed out. ** At the same operation, there can be many potential problems. Only few examples are given here. This Predictive Quality Analytic report can be used for quality training of employees too. |
||||||||||
Subsequently, Predictive Quality Analytics can be performed to foresee the quality issues pertaining to the stage of occurrences, origin of the cause, elimination technique, stage of control, responsibility, check method, and frequency of checking. After creating a detailed databank, further QE bulletins can be prepared easily.
Refer Tables 1 and 2 as examples for Risk Assessment and Predictive Quality Analytic reports, respectively.
Key benefits of Quality Engineering:
Cost Reduction for Inspection:
By using a well-made quality engineering bulletin, the product quality requirements are effectively built in the process with the involvement of direct workers. Hence many 100 per cent checkpoints can be eliminated or replaced with audit points which need fewer staffs. There can be a considerable reduction in defects and will have a good first-time-right product percentage. Factories with a larger number of quality staff are considered to be less system-driven nowadays. Saving of manpower at every opportunity should always be explored to deal with worker scarcity and to control cost.
Support the Just-in-Time concept of production:
Quality inefficiencies during processes adversely affect the Just-in-Time production concept and create whirls in the flow. Quality engineering can smoothen the flow and control inventory hold-ups besides reducing warehousing requirements.
Customers get quality confidence on manufacturers:
Many customers/buyers are upgrading their conventional QA departments to QE departments which interact more productively with the manufacturer. No customer wants the finished goods to be found with inferior quality at the end of manufacturing processes and thus unsellable. Customer’s QE departments help to identify the style criticalities and the requirements of end-customer so that the manufacturer can incorporate them sooner than later.
Each department should be objective-driven. The biggest objective or goal that can be set to the QED is to achieve “Self-inspection Permits” for the factory to inspect the goods themselves and ship. Some buyers grant these permissions after monitoring the quality performance of the factory for a period of time and save their inspection costs. QE system’s implementation can greatly support this effect.
