IDC has predicted that the AI market will be worth $50 billion plus in 2020, growing from an $10 billion market in 2016. As automation continues to penetrate all industries, apparel design software will be at the forefront of the Apparel/Fashion Industry, especially in developing countries. Today, different apparel design software are available to impact apparel styles the world over!
The AI-Apparel Relationship
Speaking hypothetically, apparel may seem like a weird choice target for AI disruption. Realistically speaking, machine learning is taking on a variety of fashion-related roles. These include tailoring, personal shopping, fashion designing, modelling, becoming your own personal stylist, etc.
A number of apparel brands already use machine learning and tailored solutions to enhance predictions and improve the search functionality on their sites. Whether this intelligence is built in-house or facilitated by a third-party, it involves training algorithms to analyze consumer behaviour with a high level of accuracy based on its understanding of a set of largely consistent and recurring variables. Today, brands focus on being super-efficient in fetching products, recommending suitable alternatives, and improving the overall Ecommerce experience as customers expect the same in an implicit way.
The tailoring software of today analyze pieces of clothing and automatically generate a cloth image on people of any shape, size or wearing any cloth accessories.
How It Works
With the help of complex innovative algorithms and machine learning, AI programs and systems are designed to perform tasks that work and react like human beings. The more data they receive, the more they interact. By constructing different realistic scenarios, the apparel design software can showcase constomer-centric desires very accurately. AI can help computers identify images and recommend the products which excite the consumer to the highest degree. Nowadays, AI can help predict rough quantities of products to store and analyze inventory based on historical sales statistics. Coupled with virtual reality and image recognition (AI) technology can be used to analyze pieces of fabric and automatically generate a template of the garment on a person of variable size. There exist many tailoring software brands that are experimenting with smart-rooms to allow customers in-store to view themselves real-time in the clothes they pick, and swap those clothes for different viewing styles. These simulations are possible at the click of a mouse and the environmental conditions such as lighting, background and context can be changed/adjusted too!
Current Applications
Market intelligence and robotics have entered the retailers’ factories and warehouses to boost productivity and efficiency. Let's see some current applications:
Fabric Pattern Inspections: Now you can automatically inspect fabric pattern aspects like weaving, knitting, braiding, finishing, and printing. Manufacturers will save on costs and time taken for inspecting the quality of the final fabric product by replacing visual inspection with using the apparel design software. Characteristics like weaving patterns, yarn properties, colors and tolerable imperfections can potentially detect minute defects (errors in knitting patterns) in the fabric, saving people from the manual task of assessing hundreds of yards of material manually.
Tolerance for Fabric Color Matching: The tailored solution establishes threshold for the difference between color between a sample and the customer requirements should be. These tolerance values are generally agreed upon internally by the manufacturer or between supplier and customer to determine if the sample passes or fails quality assurance tests.
Future Applications
Commercial use of AI tailoring software in apparel processing seems limited to only a few applications today, particularly in identifying and grading yarn. Let’s see some future applications:
While AI tailored solutions may not replace humans yet, it is a big opportunity to accelerate insights into customer preferences to align supply and demand, provide a personal customer experience, and upgrade the supply chain to create better products.
The AI-Apparel Relationship
Speaking hypothetically, apparel may seem like a weird choice target for AI disruption. Realistically speaking, machine learning is taking on a variety of fashion-related roles. These include tailoring, personal shopping, fashion designing, modelling, becoming your own personal stylist, etc.
A number of apparel brands already use machine learning and tailored solutions to enhance predictions and improve the search functionality on their sites. Whether this intelligence is built in-house or facilitated by a third-party, it involves training algorithms to analyze consumer behaviour with a high level of accuracy based on its understanding of a set of largely consistent and recurring variables. Today, brands focus on being super-efficient in fetching products, recommending suitable alternatives, and improving the overall Ecommerce experience as customers expect the same in an implicit way.
The tailoring software of today analyze pieces of clothing and automatically generate a cloth image on people of any shape, size or wearing any cloth accessories.
How It Works
With the help of complex innovative algorithms and machine learning, AI programs and systems are designed to perform tasks that work and react like human beings. The more data they receive, the more they interact. By constructing different realistic scenarios, the apparel design software can showcase constomer-centric desires very accurately. AI can help computers identify images and recommend the products which excite the consumer to the highest degree. Nowadays, AI can help predict rough quantities of products to store and analyze inventory based on historical sales statistics. Coupled with virtual reality and image recognition (AI) technology can be used to analyze pieces of fabric and automatically generate a template of the garment on a person of variable size. There exist many tailoring software brands that are experimenting with smart-rooms to allow customers in-store to view themselves real-time in the clothes they pick, and swap those clothes for different viewing styles. These simulations are possible at the click of a mouse and the environmental conditions such as lighting, background and context can be changed/adjusted too!
Current Applications
Market intelligence and robotics have entered the retailers’ factories and warehouses to boost productivity and efficiency. Let's see some current applications:
Fabric Pattern Inspections: Now you can automatically inspect fabric pattern aspects like weaving, knitting, braiding, finishing, and printing. Manufacturers will save on costs and time taken for inspecting the quality of the final fabric product by replacing visual inspection with using the apparel design software. Characteristics like weaving patterns, yarn properties, colors and tolerable imperfections can potentially detect minute defects (errors in knitting patterns) in the fabric, saving people from the manual task of assessing hundreds of yards of material manually.
Tolerance for Fabric Color Matching: The tailored solution establishes threshold for the difference between color between a sample and the customer requirements should be. These tolerance values are generally agreed upon internally by the manufacturer or between supplier and customer to determine if the sample passes or fails quality assurance tests.
Future Applications
Commercial use of AI tailoring software in apparel processing seems limited to only a few applications today, particularly in identifying and grading yarn. Let’s see some future applications:
- Determining wrinkles in fabrics is vital as it influences and decides the visual beauty of a garment. Machine-based wrinkle prediction might help textile manufacturers water down costs and time required.
- Apparel design software can also be used for determining previously hidden patterns from raw data. This involves potentially enable business to find patterns and correlations between fiber properties, process parameters, and yarn properties or among yarn properties, machine settings, and fabric performance.
While AI tailored solutions may not replace humans yet, it is a big opportunity to accelerate insights into customer preferences to align supply and demand, provide a personal customer experience, and upgrade the supply chain to create better products.
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