Model for Improving Failure Modes and Effect Analysis

Rushikesh Mahendra Bhattad* and Vaishnavi Raghuraj Baheti

D.K.T.E. Society’s Textile and Engineering Institute, Ichalkaranji-416115, Maharashtra, India.



The overgrowing need of the market and every now and again changing style has encouraged the attire business to full-fill these necessities by giving an ideal amount of best quality items with a specific end goal to keep the situation in the market. A gigantic decent variety as far as work, procedures, devices and material prompt event of different deficiencies and mistakes which should be dispensed with to create high review send out quality items. FMEA is one of the ways which encourages this disposal just before they appear to happen. The current model of FMEA isn’t good in clothing industry since this part is work concentrated and has varieties in each progression ideal from marker making up to completing and pressing of the garments. In this paper we have proposed an altered adaptation of actualizing FMEA wherein a colossal variety in the Garment industry as far as Man, Material, Machine and Mode are thought about in light of Ishikawa chart. This new model isn’t just focused on identification of deficiencies yet in addition prescribes the moves to be made for diminishing these flaws.

Keywords:  Detection, Ishikawa diagram, Occurrence, Severity etc.

1. Introduction

1.1 What is FMEA?

FMEA is a subjective and precise tool, typically made inside a spreadsheet, to enable experts to suspect what may turn out badly with an item or process. Notwithstanding distinguishing how an item or process may come up short and the effects of that failure, FMEA likewise finds the conceivable reasons for failures and the probability of failure being recognized before the event.

FMEA organizes failures as per seriousness, recurrence and perceptibility. Seriousness portrays the earnestness of the failure results. Recurrence depicts how regularly failures can happen. Perceptibility alludes to a level of trouble in identifying failures.

FMEA can be utilized from the most punctual plan and applied stages ahead through advancement and testing forms, into process control amid progressing activities for the duration of the life of the item or framework.

1.2 History

Methods for directing FMECA were depicted in US Armed Forces Military Procedures archive. By the mid-1960s, contractual workers for NASA were utilizing varieties of FMECA or FMEA under an assortment of names. Amid the 1970s, utilization of FMEA and related systems spread to different businesses. In 1971 NASA arranged a report for the U.S. geographical review suggesting the utilization of FMEA in the appraisal of seaward oil investigation. A 1973 U.S Environmental Protection Agency report depicted the use of FMEA to wastewater treatment plants. FMEA as an application for HACCP on the Apollo Space Program moved into the sustenance business as a rule.

The car business started to utilize FMEA by the mid-1970s. The Ford Motor Company acquainted FMEA with the car business. Albeit at first created by the military, FMEA methodology is currently widely utilized as a part of an assortment of ventures including semiconductor handling, nourishment benefit, plastics, programming, and social insurance.

2. Types of FMEA

2.1 Design FMEA

Design FMEA helps in the outlined procedure by distinguishing known and predictable failure modes and afterward positioning failures as per relative effect on the item.  Hence Design FMEA centres around the relative effect of the failure mode on the item.

2.2 Process FMEA

Process FMEA recognizes potential process failure modes by positioning failures and setting up needs as per the relative effect on the inner or outside client. Hence Process FMEA centres around the relative effect of the failure mode on inward or outer client.

3. When to Use FMEA?

FMEA can be used for:

  • Outlined or overhauled of the process, item or administration after quality capacity arrangement.
  • Inventive utilization of a current procedure, item or administration.
  • Before creating control gets ready for another or altered process.
  • When change objectives are gotten ready for a current procedure, item or administration.
  • When dissecting failures of a current procedure, item or administration.
  • Periodically for the duration of the life of the procedure, item or administration

4. Traditional FMEA Procedure

  1. Identify Failure modes (What could turn out badly?)
  2. Identify Failure causes (Why might the failure happen?)
  3. Identify Failure effects (What might be the outcomes of every failure?
  4. Identify the severity(S) of each reason and rate it as per the FMEA table.
  5. Identify the rate of the event (O) of each reason and give the event number from the FMEA table.
  6. Identify the identification parameter (D) as per the simplicity of location by utilizing FMEA table.
  7. Calculate the risk priority number, or RPN, which breaks even with S × O × D. Additionally ascertain Criticality by increasing seriousness by the event, S × O.
  8. Identify prescribed activities. These activities might be a plan or process changes to bring down seriousness or event. They might be extra controls to enhance recognition. Likewise note who is in charge of the activities and target fruition dates.
  9. As activities are finished, a note comes about and the date on the FMEA frame. Additionally, note new S, O or D appraisals and new RPNs.

Table 1 Ranking Method
1NoneAlmost neverAlmost certain
2Very minorRemoteVery high
3MinorVery slightHigh
4Very lowSlightModerately high
7HighModerately highVery low
8Very highHighRemote
9SeriousVery highVery remote
10HazardousAlmost certainAlmost impossible

4.1 Remark

On the off chance that the numerical esteem falls between two numbers constantly select the higher number. In the event that the group has a contradiction in the positioning quality:

  1. In the event that the contradiction is an adjoining class, normal out the distinction
  2. In the event that the contradiction hops one class. Indeed, even with one individual waiting, add up to the agreement must be come to. No normal, no greater part. Everybody in that group must have responsibility for positioning.

Risk Priority Number, which is the result of the seriousness, event and discovery evaluations is ascertained as:


  1. The RPN must be computed for each reason for failure.
  2. RPN demonstrates the relative probability of a failure mode.
  3. The higher number, the higher the failure mode.
  4. From RPN, a basic synopsis can be attracted up to feature the zones where activity is for the most part required.
  5. The RPN is re-computed after the failure has been tended to. The re-examined RPN affirms the effectiveness of the remedial dynamic attempted.

5. Modified Version of FMEA for Apparel Industry

5.1 Problem Statement

In the event that we take a gander at quality as the level of fulfillment with what we deliver, we offer, give or offer, tending to circle these clients are progressively extending, it is important to characterize the confinements that are available in the making of value. Quality Risk Management has runs by which incorporate measures, methods and instruments to recognize risks of value, rank, process, control, confine or lessen and the preventive effect of keeping their event. For instance, the generation of top-notch garment items is important to predict every single conceivable risk that can prompt decreased security when wearing garment items, for example, catches tumbling off, harmed creases or pockets, tearing, tearing interlining, and so on. When we think about attire industry-wide variety as far as Man, Material, Machine and Method are watched. Being work concentrated industry the variety in absconds happening can’t be institutionalized. By recognizing these risks, evaluate and examine the conduct of garment items to wear, with the ultimate result relies upon the capacity of makers in the view of conceivable outcomes and modification of performance items.

5.2 Methodology

Taking the above issue articulation into thought we have chosen 4 factors Man, Machine, Material and Method with 3 unique levels of each.

Table 2 Labelling Details
Level 1S -Skilled LabourUM-Uniform Material with Standard ComponentsET- Eton SystemFA- Fully Automated
Level 2SS -Semi Skilled LabourDM-Different Material with Design variationUPS-Unit Production SystemSA – Semi-Automated
Level 3US -Unskilled LabourRM-Raw Material & Design VariationsBL- Bundle LineM- Manual

5.2.1 Man

Labour assumes an imperative part in the clothing business. These labors can be classified into 3 levels as indicated by their abilities as skilled, semi-skilled and unskilled.

Skilled: They are a worry about complex tasks and are given an extraordinary preparing. The seriousness and the event of issues amid their work is negligible and they are equipped for recognizing the flaws effectively.

Semi-skilled:They are equipped for taking care of moderate level of activities. The seriousness and event are worth up to a specific level.

Unskilled:The work falling under this classification are less flexible in operational abilities. They can perform exceptionally essential tasks or else there is an enormous shot of serious shortcomings with the high event. Identification of shortcomings by them is additionally exceptionally troublesome.

5.2.2 Material

Material records for 80% of the aggregate cost and consequently legitimate choice and utilization of this is mandatory. Material varieties are extremely visited in the meantime they can’t be bargained for any reason. Activities turn out to be more unpredictable with the expansion in the material parts. They are ordered as:

Uniform Material with Standard Components: Fundamental plain texture with single shading and standard segments, henceforth while sewing this sort of material has less serious and less happening shortcomings. The recognition for this situation is simple since no coordinating of example parts is required.

Different Material with Design variety: Here the texture utilized may have a type of prints, weaves, hues and so forth so the activity ends up complex giving ascent more serious and more continuous event of flaws .identification additionally turns into somewhat perplexing.

Raw Material and Design Variations: At the point when the plan are worried about utilization of various textures, outlines, hues and so forth or the mix of them, task turns out to be exceptionally mind-boggling and there is each shot of extreme and successive deficiencies. Discovery and re retouching of this is troublesome.

5.2.3 Method

Method alludes to the sort of generation stream framework utilized as a part of the interesting business. It encouraged the property stream of material and operational parts all through the line with the goal that every one of the activities goes delivers hand and increments the effectiveness and rate of generation.

Eton: It encourages an even stream of material all through the line wherein the parts are sewed without disconnecting from the cinches consequently more exact coordinating diminishes the incessant event of extreme flaws. Identification turns out to be simple since the pays are in single anchor and simple to watch completely.

Unit Production framework: It is a framework in which a solitary garment is set aside a few minutes yet since the section of parts is done manually, blames because of loss of part or blemished coordinating can be maintained a strategic distance from. Manual identification is additionally simple for this situation.

Bundle Production System: Clipping and working number of parts together in package shape make it troublesome for quality work. There is each shot of blending and heaps of parts which may cause immense misfortune because of continuous flaws. Identification of this package isn’t simple.

5.2.4 Machine

Progressions in innovation are consistent yet the cost and accessibility of the machinery must be considered which makes it again a variety factor levelled by the modernization and effects.

Fully Automatic: It gives simplicity of working expanding the productivity and nature of generation with least level of seriousness and event of shortcomings. Discovery module makes it simple to distinguish the shortcomings mechanically assuming any.

Semi-programmed: These machines have human obstruction again giving a shot for every now and again happening serious deficiencies.

Manual: Parcel of variety in the delivered garments is watched, in addition it requires high work.

Table 3 Taguchi L9 Orthogonal Array Design

81 mixes are conceivable with these 4 unique components having 3 levels of each. To rearrange the investigation the 9 best mixes were picked by Taguchi’s orthogonal exhibit (L9) with the assistance of Minitab measurable programming. After getting the 9 mixes, these were appraised for Severity (S), Occurrence (O) and Detection (D) as indicated by their levels 1, 2 and 3 (ref. table no.3). After getting the information for S, O, and D; Taguchi’s analysis has been done to decide the rankings of various components. After distinguishing rank the Regression condition for S, O, and D were framed. Using these conditions the FMEA forecast model was outlined in Excel which is helping in failure mode analysis of existing or new clothing units for the previously mentioned 4 factors.

5.3 Regression equations

SE=2.333+ 0.0 MAN_S+ 0.3333 MAN_SS+ 0.6667 MAN_US+ 0.0 MATERIAL_DM- 1.667 MATERIAL_RM- 0.3333 MATERIAL_UM + 0.0 MACHINE_FA + 0.3333 MACHINE_M + 1.333 MACHINE_M  + 0.6667 MACHINE_SA

OC=1.500+ 0.0 MAN_S+ 0.500 MAN_SS+ 1.500 MAN_US + 0.0 MATERIAL_DM – 1.167 MATERIAL_RM- 0.333 MATERIAL_UM + 0.0 MACHINE_FA + 0.167 MACHINE_M + 1.667 MACHINE_M     + 0.333 MACHINE_SA

DE=1.333+ 0.0 MAN_S+ 0.3333 MAN_SS+ 0.6667 MAN_US+ 0.0 MATERIAL_DM0.6667 MATERIAL_RM- 0.3333 MATERIAL_UM + 0.0 MACHINE_FA + 0.3333 MACHINE_M + 1.333 MACHINE_M + 0.6667 MACHINE_SA

6. Conclusion

So far we endeavored to abridge the variables in Apparel industry which contribute significantly to the assessment of deficiencies. The fundamental driver, effects, simplicity of perceptions and the reasonable major for each conceivable failure mode. Our model is a procedure particular, is much material for array since the items accompany immense contrast in texture, design, faster and so forth henceforth making this a long procedure. So considering the variables influencing each procedure made it easy to judge. As opposed to finding the blame we made our analysis based on the elements that influence these shortcomings straightforwardly or in a roundabout way. The range for the Severity, Occurrence and Detection record can be chosen by the required quality and prioritization for the zone of extreme effect cause should be possible to take out the happening misfortune. As indicated by the necessity of the fundamental factors in a procedure each time another table for rating and blend is to be outlined.

7. Reference

  1. Dr. Gordana Colovic and Dr. Danijela Paunovic, Application Quality Methods in Garment Production,
  2. Taguchi methods,
  3. Video tutorial FMEA by Narender Sharma
  4. FMEA Failure Mode and Effects Analysis,

©2018 by the authors.This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Please cite this article as: Rushikesh Mahendra Bhattad,Vaishnavi Raghuraj Baheti (2018) Model for Improving Failure Modes and Effect Analysis. Journal of Textile and Clothing Science.
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