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Manufacturing excellence: Road to industry 4.0

While the trends of consumer behavior in the fashion business is changing disruptively for a decade, the COVID-19 outbreak in 2020, Geo-Political situations in 2021 and currency inflation in 2022 took this paradigm shift into a roller coaster journey while any prediction is unsafe. Yet, global fashion retailers and manufacturers have identified the necessity of Hybrid work modules, digitization and automation. But deciding on this transformation is critical for every case either in a similar business or a different one.

Manufacturing excellence Road to industry 4.0
Figure: Engineering technology and industry 4.0 smart factory concept with icon graphic showing automation system by using robots and automated machinery controlled via internet network.

This article triggered a generalized methodology to answer the two vital questions ‘Why’ & ‘How’. Furthermore, it triggered into more on strategic footprints, potential barriers and way forward toward digital transformations based on real-life situations in different manufacturing regions and cultures.

Global fashion retailers and manufacturers have identified a few common areas to optimize to survive and grow together under a WIN-WIN platform, which are-

1> Sustainable quality in service & product

2> Speed to source, design, manufacture & delivery

3> Effective strategy and efficient manufacturing

4> Re-skill people for a hybrid business model

Here comes the need for manufacturing excellence in business intelligence, big data analytics, and design flexibility & sustainable sourcing, inventory turnover ratio, supply chain agility and manufacturing flexibility.

While defining the needs of excellence, requires a diagnosis of a few things first, which are-

1> Geological position & Socioeconomic factors.

2> Min Wages and GDP of the region.

3> Backward linkage sourcing facility.

4> IRR (Internal rate of return), COGS (Cost of selling goods), DSCR (Debt service coverage ratio), ROI (Return of investment) & PBP (Payback period).

Consequently, needs of excellence are defined, measured and analyzed through a methodological manner to comply end-to-end fashion cycle based on the product varieties, which are stated below-

END-TO-END-fashion-cycle

The above end-to-end fashion cycles are different from case to case. Thus the strategies and actions are different, consumer behaviors and service/quality standards are different and the need for speed is different either. Retailers and manufacturers then set their transformation strategies and cascade them down to execution models. The transformations are usually planned into three major segments, which are-

1> Business transformations

2> People transformations

3> Process & workshop transformations

While defining transformation roadmaps, we follow some common methodological tactics to achieve desired manufacturing excellence goals, which are-

fashion-upstream

Keeping the above basics in mind, ‘Manufacturing Excellence’ tactics usually follow 4 major methodological protocols to comply the high-level strategic transformation goals and their execution models, which are-

fashion-process-digitalization

While following the above 4 steps, different segments/stakeholders of operations are wisely engaged in the manufacturing excellence steps, which is extremely vital to define, measure, analyze and control. A generalized cross matrix of such engagement is as below-

business-fashion-mapping

The game is inside this cross-matrix engagement. Sourcing, designing and operations experts have to conduct a SWOT first, find barriers and opportunities secondly and set execution and control tactics thirdly. They have to clearly define the short & long-term goals through feasibility analysis and ROI, to achieve and delegate the responsibility accordingly through a clear conceptual framework, small steps towards achieving goals and proper training. Every step must be measured, analyzed and improvised as needed in real-time.

Why does manufacturing excellence fail?

During these unpredictable business trends and disruptive changing situations, many companies think investing in digital solutions and/or automation may bring the desired transformation goals. Consequently, some random digitization and automation investment are taken place and no visible improvements are seen. Stakeholders need to assess the need for digitization or automation through a clear-cut agenda and methodological approach. Then process and people optimization is a must with a visible measuring system. Moreover, the implementation team and the user group should be aligned with the same agenda and trained properly. Consequently, the need for automation becomes realistic and sustainable. This is how the ‘Manufacturing Excellence’ drive will sustain and deliver visible results.

Few low hanging fruits examples for driving “Manufacturing Excellence”

A> Case:01

VOC: Unpredictable shade variations in knit garments.

CTQ: Controlling shades during fabric manufacturing.

Root Causes

1> Poor selection of yarn

2> Uneven shades after dying due to improper amount of knitted gray fabric feeding in nozzles.

Why does manufacturing excellence fail

Solutions

1> Dying machine plan should follow the need of the fabric cut plan by construction, color, size and qty.

2> Making knitted roles based on reel speed & nozzle loading capacity to minimize the number of roles in each nozzle of the dying machine and keep a similar weight and number of roles for each nozzle.

3> Manage batch plan following the fabrics cutting plan.

B> Case: 02

VOC: Higher washing rejections in denim garments.

CTQ: unpredictable fabric defects in the same style of garments.

Root causes

1> Higher rates of particular defects in inspection-passed fabrics which vary from batch to batch.

defect-contribution-suppliers

Solutions

1> Analyze fabric inspection results through SPC and Pareto chart. Conduct more inspections if a particular defect rate is more than 30% in inspected roles.

2> Segregate roles by top defectives and set separate making and washing plans through trial and error. For example, if 30% of garments are made with 120 roles which have 48% potential knots, the washing abrasions should be minimized to reduce the chances of creating holes after wash. Consequently following the defined recipe based on other top defectives in sewn garments will remarkably reduce the total number of wash rejections.

C> Case:03

VOC: Measurement discrepancy and unpredictable variations during sewing garments.

CTQ: The trial production pattern/marker adjustment

Root cause

1> the development pattern/marker, approved garment sample and bulk pattern/marker mismatch.

2> during making the first sample, the given patterns are not properly adjusted as sample men are usually equipped with scissors, thus they do some necessary small adjustments during sewing.

Solutions

fabric-cutter auto fabric feeding

1> Use single pcs auto cutter with auto fabric feeding and digital marker projection for precision cutting.

2> Remove scissors from sample sewers, thus every adjustment should reflect to the original pattern and marker. It may increase some sample-making lead time, yet can offset huge measurement variations and cost of quality which eventually increases the efficiency of making.

D> Case: 04

VOC: Higher cost of manufacturing

CTQ: Reducing the cost of poor quality & increasing making efficiency

Root Causes

1> Lack of data tracking and big data analysis during making garments.

2> Higher repairing rate and nonproductive time during making garments.

3> Higher Man: Machine ratio during making garments.

Solutions

Power BI-Planning software for manufacturing planning

1> Use advanced excel spreadsheets/Power BI/Planning software for manufacturing planning and tracking critical path of operations end-to-end.

2> Use barcode/QR/RFID based real-time tracking system in production

 

RFID based real time tracking system RFID based real time tracking system in production

3> Analyze top the defects/defective processes, Nonproductive times & Machine breakdown reasons in real-time and take rapid actions. Start with small improvements daily basis with real-time précised and accurate analyzed data sets and perform continuous improvements.

4> Train mid-management and workers on using IoT, smartphones and digital tools to ease their daily work routine.

5> Install zig-making techniques, advanced machinery and pressing equipment to simplify the making process and increase efficiency.

Install zig making techniques

6> Install automatic transportation systems like hangers, and conveyer belts to manufacturing units to minimize handling motions, and reduce changeover complexity while making long garments or small size orders and there is a higher rate of changeover.

Conclusion

Engr. Anisul Hoque Ansari
Author: Engr. Anisul Hoque Ansari APRM™ I CSSBB™ I TPS™ I CBSI™
Manufacturing Excellence professional.

There are thousands of low-hanging fruits to rip in terms of driving ‘Manufacturing Excellence’ through which we can get a remarkable improvement in business performance. Only thing is to DEFINE>MEASURE>ANALYZE in a systematic manner & IMPROVE>CONTROL through digitization and automation and control them through structured big data analysis.

Courtesy: McKinsey & Company; Techzen, ENA, YYC Technology ltd., KAEMI technologies Ltd.

If anyone has any feedback or input regarding the published news, please contact: info@textiletoday.com.bd

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