MIL Asia Pacific Publishing Engine

Source: Government of India

Posted On: 26 MAR 2025 4:25PM by PIB Delhi

A total of 10 Implementing Partners having office address in Maharashtra are empaneled under Samarth scheme in last three years i.e. 4 IPs in FY 2021-22 and 6 IPs in FY 2023-24.

The RFP was floated on 06.12.2024 for empanelment of new Implementing Partner. Under this RFP, 13 proposals have been received from applicants having office address in Maharashtra. These proposals are under consideration.

The details of beneficiaries trained (pass) and placed under Samarth scheme during the last three years, category-wise are provided below and district-wise details of Maharashtra are also given below.

The Textiles Committee which is the Resource Support Agency (RSA) under SAMARTH scheme conducts Training of Trainers (ToTs) and Training of Assessors (ToAs) on regular basis as these activities are demand driven to the textile industry.

There is no state wise allocation of target under Samarth scheme. However, Implementing Partner may open training centre across the country.

The details of beneficiaries trained (pass) and placed under Samarth scheme during the last three years, Category wise are as given below:

S. No.	District	Gen	OBC	SC	ST	Total
1	Beed	115	0	0	0	115
2	Kolhapur	293	69	54	1	417
3	Latur	186	3	50	1	240
4	Mumbai	207	296	188	0	691
5	Nagpur	852	182	1,012	172	2,218
6	Nanded	25	0	64	0	89
7	Nashik	26	0	0	0	26
8	Palghar	153	10	89	86	338
9	Pune	14	0	27	6	47
10	Raigad	132	0	53	24	209
11	Ratnagiri	70	0	0	0	70
12	Sangli	117	22	0	0	139
13	Satara	60	0	0	0	60
14	Thane	1,521	270	1,763	966	4,520
	Total	3,771	852	3,300	1,256	9,179

The details of beneficiaries trained (pass) and placed under Samarth scheme during the last three years, District wise in Maharashtra are as given below:

S. No.	District	Trained (pass)	Placed
1	Beed	115	96
2	Kolhapur	417	380
3	Latur	240	238
4	Mumbai	691	316
5	Nagpur	2,218	1,912
6	Nanded	89	89
7	Nashik	26	26
8	Palghar	338	308
9	Pune	47	43
10	Raigad	209	176
11	Ratnagiri	70	70
12	Sangli	139	139
13	Satara	60	60
14	Thane	4,520	3,920
	Total	9,179	7,773

This information was provided by THE MINISTER OF STATE FOR TEXTILES SHRI PABITRA

MARGHERITA in a written reply to a question in Lok Sabha today.

***

DHANYA SANAL K

 (Lok Sabha US Q4083)

(Release ID: 2115281) Visitor Counter : 16

Source: Government of India

Posted On: 26 MAR 2025 4:25PM by PIB Delhi

Government provides financial support to various Export Promotion Councils and Trade Bodies under Market Access Initiative Scheme implemented by Department of Commerce for organising and participating in trade fairs, exhibitions, buyer-seller meets etc. at national and international levels so that Indian exhibitors get benefits of global exposure.

The major eligible items of expenditure for organising / participating in Fairs, Exhibitions and Buyer Seller Meets Abroad under MAI Scheme are as under:

1. Venue Cost, including Participation charges/ fee and organising expenses;
2. Publicity Cost incurred on promotion/ marketing/publicity, including digital marketing for buyer participation;
3. Cost of catalogue/printed and digital material, including cost of e-catalogue/ e-brochure/ web-banners/ online advertisement and other materials including its design and development/ creation;
4. Translation and Interpreters charges;
5. Expenditure towards freight charges of exhibits;
6. Reimbursement of air-fare to exporting companies with an f.o.b. value of exports below Rs.50 crore in the preceding financial year.
7. Any other specific component approved by the Empowered Committee.

This information was provided by THE MINISTER OF STATE FOR TEXTILES SHRI PABITRA MARGHERITA in a written reply to a question in Lok Sabha today.

*******

DHANYA SANAL K

DIRECTOR

(Lok Sabha US Q4134)

(Release ID: 2115282) Visitor Counter : 16

Source: Government of India

Posted On: 26 MAR 2025 4:25PM by PIB Delhi

Ministry of Textiles through Office of Development Commissioner (Handlooms) promotes Handloom products of the country including Bargarh by implementing following scheme:

1. National Handloom Development Programme;
2. Raw Material Supply Scheme;

• Under the above schemes, financial assistance is provided to eligible handloom agencies/weavers for raw materials, procurement of upgraded looms & accessories, solar lighting units, construction of workshed, skilling, product & design development, technical and common infrastructure, marketing of handloom products in domestic & international markets, concessional loans under weavers’ MUDRA scheme and social security etc.

· Assistance in establishing international marketing linkages to suitable Apex/Primary handloom cooperative societies, corporations, producers’ companies, handloom awardees, exporters, other talented weavers etc. who are producing exclusive exportable handloom products.

· Market penetration through organisation/participation in international fairs/exhibitions, big ticket events, Buyer Sellers Meet, Reverse Buyer Sellers Meet etc., for export promotion of handloom products. Publicity and brand development through India Handloom Brand (IHB), Handloom Mark (HLM) and other measures.

· Raw Material Supply Scheme (RMSS) is being implemented throughout the country including Bargarh to make available yarn to handloom weavers. Under the scheme, fright charges are reimbursed for all types of yarn; and component of 15% price subsidy is there for cotton hank yarn, domestic silk, wool and linen yarn and blended yarn of natural fibres.

• Sambalpuri Bandha Saree & Fabrics is also registered under the Geographical Indication (GI) of Goods (Registration & Protection) Act 1999.

This information was provided by THE MINISTER OF STATE FOR TEXTILES SHRI PABITRA

MARGHERITA in a written reply to a question in Lok Sabha today.

****

DHANYA SANAL K

DIRECTOR

(Lok Sabha US Q4081)

(Release ID: 2115283) Visitor Counter : 15

Source: Government of India

Posted On: 26 MAR 2025 4:24PM by PIB Delhi

Under the National Technical Textiles Mission (NTTM), total 168 Research & Development projects of Rs. 509.8 crore have been approved till date. Project Completion Reports of    06 R&D projects have been received, out of which 02 projects have been closed.

The research areas under NTTM includes fundamental research in thrust areas of speciality fibre like Carbon Fibre, Aramid Fibre, Nylon Fibre, and Composites & application based research in geotextiles, agro-textiles, medical textiles, mobile textiles and sports textiles and development of biodegradable technical textiles. 

The specific research projects in speciality fibers includes the development of carbon fiber, meta-aramid fibers, high-performance gel-spun Ultra-High Molecular Weight Polyethylene (UHMWPE), flame-retardant Nylon-66 yarn, and bio-component fibers. Further, Mission is focusing on applications of geotechnical textiles for high-speed railway networks, roads, sub-zero temperature infrastructure, erosion control in North East Region (NER) & soft soils areas and structural geotextiles made from textile waste, etc.

With the outcome of these research projects, the mission aims to improve penetration level of technical textiles in the country and to create an ecosystem for manufacturing of technical textiles through indigenous development of critical application areas and innovative solutions.

This information was provided by THE MINISTER OF STATE FOR TEXTILES SHRI PABITRA

MARGHERITA in a written reply to a question in Lok Sabha today.

****

DHANYA SANAL K

DIRECTOR

(Lok Sabha US Q4061)

(Release ID: 2115280) Visitor Counter : 24

Source: Republic of China Taiwan

The AI-driven Self-Navigating Miniature Serpentine Robotic System (AiSNMSR), developed by ITRI, addresses key challenges in Natural Orifice Transluminal Endoscopic Surgery (NOTES) such as limited operational space, small orifice diameters, excessive bleeding, and risks associated with punctures, infections, and inefficient cleaning. This award-winning system integrates omnidirectional bending, real-time tactile/haptic feedback, self-navigation, and modular tool-swapping capabilities, allowing surgeons to perform precise, efficient, and safe procedures with ease.

AiSNMSR is composed of a main controller, a navigation module with tactile/haptic sensing, an endoscope equipped with a CMOS camera, and additional devices customized for specific medical applications. The system provides surgeons with tactile/haptic feedback for precise navigation and mimics human tactile perception, enhancing operational control. The flexibility of our robotic endoscope allows omnidirectional bending up to 210 degrees. Additionally, our AI-enhanced processing provides real-time imaging data for accurate positioning, obstacle recognition, and environmental adaptation, ensuring both safety and precision during surgery.

The AiSNMSR system could be used in a wide range of surgical fields, such as gastroenterology, obstetrics and gynecology, urology, colorectal surgery, neurosurgery, and gastrointestinal surgery, with the capabilities to reduce postoperative pain, shorten recovery times, minimize complications, increase surgical success rates, and improve overall patient outcomes. The system has been validated through collaboration with the Chief of Thoracic Surgery at National Taiwan University Hospital, and this innovative robotic system represents a leap forward in minimally invasive surgical technology.

Source: Republic of China Taiwan

ITRI’s MOSAIC (Memory-cube Operability in a Stacked AI Chip for Generative AI) won a 2024 R&D 100 Award in the IT/Electrical category. MOSAIC offers a solution to address the cost and scalability challenges associated with AI/GAI chips. It integrates logic computation and memory, enabling a flexible and scalable 3D stacking technology. MOSAIC’s innovative 3D stacking chip design significantly reduces the transmission distance between chips from micrometers (micrometre) to nanometers (nm), cutting heat generation by 90% and reducing costs by 80%. With modular, multi-layer, and scalable features, it meets the application needs of various AI products, ranging from portable devices and edge computing units to HPC servers. By employing flexible and more efficient wafer manufacturing solutions, AI systems can achieve enhanced performance and deployment capabilities while concurrently lowering energy consumption.

MOSAIC was developed in collaboration with PSMC (Powerchip Semiconductor Manufacturing Corporation), a semiconductor foundry that specializes in providing wafer manufacturing services for both logic and memory applications. The prototype of MOSAIC was created from two 12-inch wafers fabricated utilizing PSMC’s 40nm logic and 25nm DRAM processes. It employs wafer stacking technology to simultaneously transfer data between logic circuits and DRAM.

Source: Republic of China Taiwan

The tapping process of Basic Oxygen Furnace (BoF) in the steel industry has numerous bottlenecks and obstacles, including energy use, carbon emissions, constant equipment or technology updates, and labor-intensive processes. ITRI and China Steel Corporation developed the Digital Twin System for the Tapping Process (DiTwS-TP) solution specifically for improving the tapping process. This system utilizes six intelligence-base models that are based on prior experience, AI-module and simulation results. The main purpose of this system is to increase transparency in the tapping process and assist tapping operators in precisely controlling the process.

DiTwS-TP is software that accurately predicts the behavior of liquid steel. By simulating and monitoring production processes, it optimizes efficiency and minimizes costs. Its predictive capabilities enable preemptive optimization of turntable procedures, revolutionizing steel manufacturing with enhanced quality control. The taping process digital twin environment is a system that combines virtual and real-time simulation to provide a synchronized experience. Unlike the previous traditional manufacturing method, which had issues with labor consumption, difficulty in transferring experience, and probable manufacturing failures, this simulation system can be employed in the current system.

By building a digital twin model of the equipment, manufacturers can track its operating status in real time, collect various sensor data, and use artificial intelligence algorithms to predict faults and preventive maintenance, thereby reducing the equipment failure rate and increasing productivity. By using digital twins for simulation training and safety management, workers can gain a deeper understanding of production equipment and operating procedures, thereby improving workplace safety and efficiency.

Source: Republic of China Taiwan

With shrinking transistor sizes, a shift from 2D to 3D structures, and the adoption of metal materials in 2nm chip production, the limitations of current optical measurement become more apparent. Consequently, critical dimensions cannot be accurately measured, directly impacting yield and leading to poor outcomes. The In-Line X-Ray Critical Dimension Metrology System (XRCD) is a specialized system utilized in the semiconductor manufacturing industry for the purpose of measuring critical dimensions using X-ray technology. During semiconductor manufacturing processes, these systems commonly monitor the dimensions and configuration of microstructures to ensure that the produced components meet specified specifications and yield.

ITRI and NanoSeeX have developed the first In-Line X-Ray Critical Dimension Metrology System (XRCD). A perfect balance between measurement area ( 1 micrometre) can be achieved with sufficient signal intensity by combining with highly efficient focusing optical with a specific soft X-ray wavelength. Additionally, utilizing an exclusive background subtraction patent, specific target signals can be extracted and analyzed from complex spatial signals generated by three-dimensional structures.

In signal analysis, NanoSeeX has pioneered the integration of interference signals from interface reflections and high order mode signal techniques, along with multi-physics models. This approach, compared to traditional Fourier transform signal analysis, not only enables more precise thickness measurements but also reduces correlations between fitting parameters in complex 3D structures. With AI-driven machine learning, the measurement accuracy of 3D complex structure CD can reach