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Fashion for Good Museum publishes Legacy Report (c) Camilla Rama and Hyunji Kim
05.06.2024

Fashion for Good Museum publishes Legacy Report

The Fashion for Good Museum publishes its legacy document. The report was prompted by the museum’s closure on June 5th, 2024. It represents the museum’s mission, summarising invaluable insights gathered over six years and key results such as reaching 115.000 visitors and creating a dedicated community of more than 250.000 followers online. Committed to transparency and collaboration, Fashion for Good shares its reflections, tools, and transferable learnings, as well as the future of its collections and next steps, continuing to inspire positive change within the fashion ecosystem. All information can be accessed on the Fashion for Good website for continued use and benefit of educators, the cultural sector, and the wider public.

The Fashion for Good Museum publishes its legacy document. The report was prompted by the museum’s closure on June 5th, 2024. It represents the museum’s mission, summarising invaluable insights gathered over six years and key results such as reaching 115.000 visitors and creating a dedicated community of more than 250.000 followers online. Committed to transparency and collaboration, Fashion for Good shares its reflections, tools, and transferable learnings, as well as the future of its collections and next steps, continuing to inspire positive change within the fashion ecosystem. All information can be accessed on the Fashion for Good website for continued use and benefit of educators, the cultural sector, and the wider public.

Looking back on its journey, the Fashion for Good Museum celebrates achievements such as hosting 115.000 visitors, including 8.000 students from 200 schools, curating 13 exhibitions, offering over 75 events, launching 4 educational programmes, reaching both current and future generations, and inspiring many to drive change in the fashion industry. With an earned media value of over 46 million Euros through press coverage since 2017, Fashion for Good's influence has been significant, evident in its 250.000 social media followers and 15.000 newsletter subscribers.

The report fulfils the promise Fashion for Good made in 2017 – to share their journey, learnings, and most impactful activities with the world. Within these pages, readers will discover reflections on their messaging, insights about creative partnerships with entities such as Lowlands Festival, Dutch Design Week, and Museumnacht to case studies of pioneering exhibitions. Their programming was created around themes and topics, such as the untold stories around cotton, circularity, and the future of biomaterials to educate and inspire visitors, ultimately empowering them to take action themselves.

Reflecting on the output of the museum during its short existence, as well as its footprint and wide reach, while acknowledging the challenges encountered during its establishment and development, Fashion for Good distilled six key lessons from Fashion for Good's sustainable museum practices:

  • Recognition of Broader Shift: There is a wider movement towards sustainability in the museum sector, exemplified by Fashion for Good and the new ICOM definition.
  • Storytelling for Societal Change: Cultural institutions are crucial in driving societal change in fashion consumption through storytelling.
  • Innovation through Limitations: Embracing organisational limitations can stimulate innovation in museum collection management and education.
  • Audience Engagement: Understanding and expanding the core audience is essential for effective engagement in sustainability initiatives.
  • Measuring Impact: It's challenging to measure impact for organisations with social missions, requiring clear success criteria.
  • Establishing a Sustainability Framework: Defining sustainability within context is fundamental for organisational sustainability efforts.
More information:
Fashion for Good textile exhibition exhibition space
Source:

Fashion for Good

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09.01.2023

Shelton Vision AI: Tailored machine learning solutions for the textiles industry

Over the past three years, a dedicated AI development team at BTMA member Shelton Vision has been developing tailored machine learning solutions for the textiles industry.

The aim has been to elevate the detection process and the accuracy of naming and grading subtle defects in textiles, in real time within production environments.

“Big Data ‘off-the-shelf’ systems such as those behind technolgies like facial recognition and Google Maps involve reading many thousands of single images each second and simply take too long to accumulate sufficient data for what’s required in this specific case,” says Shelton Vision CEO and Managing Director Mark Shelton. “A feature of the textile industry is that in many sectors, the product range changes several times within a year and it is not uncommon to have to inspect hundreds, if not thousands of different styles in a year based on precise settings.”

In terms of defect types, he adds, there may typically be over 100 that need to be accurately detected, classified (named) and graded in real time.

Over the past three years, a dedicated AI development team at BTMA member Shelton Vision has been developing tailored machine learning solutions for the textiles industry.

The aim has been to elevate the detection process and the accuracy of naming and grading subtle defects in textiles, in real time within production environments.

“Big Data ‘off-the-shelf’ systems such as those behind technolgies like facial recognition and Google Maps involve reading many thousands of single images each second and simply take too long to accumulate sufficient data for what’s required in this specific case,” says Shelton Vision CEO and Managing Director Mark Shelton. “A feature of the textile industry is that in many sectors, the product range changes several times within a year and it is not uncommon to have to inspect hundreds, if not thousands of different styles in a year based on precise settings.”

In terms of defect types, he adds, there may typically be over 100 that need to be accurately detected, classified (named) and graded in real time.

“Added to this is the need to ‘filter out’ the random occurrence of ‘non defects’, such as loose threads, lint and dust on the surface – the number of which can be higher than actual defects – and it is clear that a bespoke system is required.”
The development team has consequently established metadata for identifying defect properties, enabling the successful identification of faults from a much smaller number of images.

“The system employs a unique combination of machine learning for automated style training and novel algorithms for defect detection, to provide high quality images for the AI real time defect classification and grading software,” Shelton explains. “Due to the inherent variation in fabric features – raw materials, construction, texture, colour and finishes, as well as the differing product quality standards in value chains and the regional variations in what defects are called – our AI engine uses models built for each individual company or group of companies, or product value chain.”

The AI models are constructed so that the user operatives can populate them with their own data produced by the vision system or by obtaining defect images from another imaging source (eg a mobile phone camera).  

The occurrence of defects is sporadic and many defect types occur infrequently, although when they do, they can have severe consequences. These scenarios re-enforce the need for the AI engine to be quickly set up and able to operate accurately with limited data sets of typically between 30 and 50 good quality images per defect type.

A further feature is a tool enabling the user to periodically ‘clean up’ the AI data during the set up phase. This is used to resolve conflicting data and to correct mis-named images.

Generally, the highest cost component of fabric production is the raw material and in addition to finished product inspection, a cost effective use for vision systems is in process operation.

Generally, the highest cost component of fabric production is the raw material and in addition to finished product inspection, a cost effective use for vision systems is in process operation.

“There is a need for the real time detection of defects that are being created in separate processes, such as printing or coating and for real time automated systems that can accurately determine the defects and their severity and provide a reliable signal for an operative to rectify the issue, This can result in considerable savings.

Prior to Shelton introducing powerful customised machine vision and real time defect classification, the only systems available were those that required manual sifting through vast numbers of images, which included both real defects and ‘non defect’ images. The task was very often overwhelming and did not provide much benefit beyond manual fabric inspection.

More information:
Shelton Vision fabric inspection
Source:

AWOL for British Textile Machinery Association (BTMA)

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EFI MarketDirect StoreFront for Events and Exhibitions
21.06.2021

EFI MarketDirect StoreFront for Events and Exhibitions

– A brand-new Rentals and Reservations module for EFI™ MarketDirect StoreFront web-to-print software from Electronics For Imaging, Inc. helps print businesses, marketing service providers and other organisations manage resources, assets and products in inventory and rent them out for events and exhibitions. This first-of-its-kind print eCommerce innovation gives users the ability to define an event, its dates and location, then identify which products are available for that time – providing cost by the hour, day or month – and check out, securing the resources from the print provider.

The newly available module addresses a re-emerging need for graphics and marketing support for tradeshows, conferences and other events. It also follows an accelerated schedule of enhancements to the award-winning MarketDirect StoreFront platform, including:

– A brand-new Rentals and Reservations module for EFI™ MarketDirect StoreFront web-to-print software from Electronics For Imaging, Inc. helps print businesses, marketing service providers and other organisations manage resources, assets and products in inventory and rent them out for events and exhibitions. This first-of-its-kind print eCommerce innovation gives users the ability to define an event, its dates and location, then identify which products are available for that time – providing cost by the hour, day or month – and check out, securing the resources from the print provider.

The newly available module addresses a re-emerging need for graphics and marketing support for tradeshows, conferences and other events. It also follows an accelerated schedule of enhancements to the award-winning MarketDirect StoreFront platform, including:

  • AutoEngage – an abandoned shopping cart feature that drives increased engagement and transaction completion rates;
  • MarketDirect Fulfillment, a modular and flexible inventory management and warehousing solution that helps printers quickly and easily build and manage fulfilment tasks for their clients; and
  • Google® Tag Manager and Analytics tools that make measuring web to print performance easier than ever.
More information:
EFI textile printer digital digital printing events
Source:

EFI

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