Think Dignity International https://thinkstudio.in Affordable Ai Softwares Sat, 01 Aug 2020 06:25:14 +0000 en-US hourly 1 https://wordpress.org/?v=5.4.1 Marketing https://thinkstudio.in/marketing-sidcul-haridwar/ https://thinkstudio.in/marketing-sidcul-haridwar/#respond Wed, 15 Jul 2020 13:42:31 +0000 https://thinkstudio.in/?p=212237 Marketing Team Offices: Our Teams In  India and Canada /USA Mr Sanjeev Sharma (Marketing Head) With more than 20 years of marketing and sales experience , he is working to increase presence of our firm in SIIDCUL (Haridwar, Roorkee, Kashipur and Dehradun) , people appreciate how he never over promises and gives you both sides of […]

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Marketing Team Offices:

Our Teams In  India and Canada /USA

Mr Sanjeev Sharma (Marketing Head) With more than 20 years of marketing and sales experience , he is working to increase presence of our firm in SIIDCUL (Haridwar, Roorkee, Kashipur and Dehradun) , people appreciate how he never over promises and gives you both sides of story.

Address: HSE Enterprises, Shopping Centre ,  Shivalik Nagar, BHEL Haridwar UK, India

Phone Number: +91-6399935149

Mr. Abhishek Vidyarthi ( Founder TDI )  Can be reached at tdi@thinkstudio.in

Address: U 501, Haridwar Greens , Navoday chowk, Haridwar UK, India

Ms. Sasha Tanoushka (USA and Canada)

Sasha looks at our sales and marketing in USA and Canada, she has been entrusted to develop our market share in areas like app development and SEO functionalities. She can be reached at +1(250-507-0960)

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developers https://thinkstudio.in/developers/ https://thinkstudio.in/developers/#respond Wed, 15 Jul 2020 13:15:09 +0000 https://thinkstudio.in/?p=212231   World Class Developers Our core developers are certified Stanford professionals in Machine Learning and Artificial Intelligence. 1- Mayank Dhiman – (4 years Experience , Stanford Certified) B.Tech from THDC Engineering College, throughout topper in his career decided to join TDI in year 2017. Today he is a respected contributor to all projects and is […]

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World Class Developers

Our core developers are certified Stanford professionals in Machine Learning and Artificial Intelligence.

1- Mayank Dhiman – (4 years Experience , Stanford Certified)

B.Tech from THDC Engineering College, throughout topper in his career decided to join TDI in year 2017. Today he is a respected contributor to all projects and is active on many coding platforms, like Kaggle , Quora, stackexchange. He has on his own worked on many advanced Algorithms which include GAN ( Generative Adversarial Networks) . He is fluid coder in Python, Java , SQl and also is comfortable in making android apps.

2- Adrian  Munguia – (20 Years Experience)

I am a recognized artificial intelligence (AI) expert with 20 years of experience creating solutions and business success in Health Care, Manufacturing, Automation, Defense, Marketing, and more.

SWE, DL, ML, CV, AI, OOA/OOP, Agile.

WHAT I DO:

▶ I help people build AI-intensive products.
▶ I help companies solve difficult problems with the right algorithms and AI approaches.
▶ I help companies hire, train, and structure in-house AI teams.
▶ I advise governments looking to embrace AI and assist decision-making, provide knowledge, difficult to obtain know-how, support from a world-class team, and access to many key resources from organizations around the world!

WHO I WORK WITH:

With anyone looking to learn, teach, adopt, or implement AI successfully in:

▶ Healthcare
▶ Retail & E-commerce
▶ Fintech
▶ Logistics and Transportation
▶ Manufacturing
▶ Defense
▶ Law Enforcement
▶ Entertainment, Gaming or Marketing

WHY IT WORKS:

▶ Working with me will get you the most efficient, effective, transparent, and cost-effective AI services comprised of R&D and product-oriented engineering, AI models that meet client specs and professionally engineered and deployable software.

WHAT MAKES ME DIFFERENT:

▶ I am the only AI resource around that has 20 years of industry success as part of innovative startups and world-famous Fortune 500 companies.

▶ Contributed important CV inventions leading to US patents: 9177225, 9336459, 9317778.

▶ Skilled problem-solver with an accurate sense of the algorithms that need to be improved, and the CV and ML approaches to be modified to meet contractual rates and obtain customer sign-off.

3- Abhishek Vidyarthi ( Stanford Certified Ai and ML , 2018)  

His strength is less of coding and more of understanding the behavior side of Technology, curious about the way people consume technology makes him leagues ahead in understanding clients key issues, be it about rolling out new product, or business process change. Abhishek always tries to match User interface with end consumer . He focuses on cost reduction and guides entire operations to deliver world class projects to clients both in B2B segment and B2C segment.

You can trust us on quality and Price.

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Overall Equipment Effectiveness (OEE) https://thinkstudio.in/overall-equipment-effectiveness-oee/ https://thinkstudio.in/overall-equipment-effectiveness-oee/#respond Sat, 02 May 2020 12:21:30 +0000 https://thinkstudio.in/?p=212107 OEE scores provide a very valuable insight – an accurate picture of how effectively your manufacturing process is running. And, it makes it easy to track improvements in that process over time.

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The simplest way to calculate Overall Equipment Effectiveness (OEE) is as the ratio of Fully Productive Time to Planned Production Time. Fully Productive Time is just another way of saying manufacturing only Good Parts as fast as possible (Ideal Cycle Time) with no Stop Time. Hence the calculation is:

OEE = (Good Count × Ideal Cycle Time) / Planned Production Time

Here, Fully Productive Time is actual production time after all losses are subtracted, Planned Production Time is the total time that equipment is expected to produce, Good Parts meet the quality standards, Ideal Cycle Time is the minimum time to produce one part, and Stop Time also called Down Time is all the production time when the production was halted because of planned or unplanned stops.

Although this is an entirely valid calculation of OEE, it does not provide information about the three loss-related factorsAvailabilityPerformance, and Quality. For that – we use the preferred calculation.

PREFERRED CALCULATION

The preferred OEE calculation is based on the three OEE FactorsAvailabilityPerformance, and Quality.

Calculate Overall Equipment Effectiveness by multiplying Availability, Performance, and Quality
OEE is calculated by multiplying the three OEE factors: Availability, Performance, and Quality.

Availability

Availability takes into account all events that stop planned production long enough where it makes sense to track a reason for being down (typically several minutes).

Availability is calculated as the ratio of Run Time to Planned Production Time:

Availability = Run Time / Planned Production Time

Run Time is simply Planned Production Time less Stop Time, where Stop Time is defined as all time where the manufacturing process was intended to be running but was not due to Unplanned Stops (e.g., Breakdowns) or Planned Stops (e.g., Changeovers).

Run Time = Planned Production Time − Stop Time

Performance

Performance takes into account anything that causes the manufacturing process to run at less than the maximum possible speed when it is running (including both Slow Cycles and Small Stops).

Performance is the ratio of Net Run Time to Run Time. It is calculated as:

Performance = (Ideal Cycle Time × Total Count) / Run Time

Ideal Cycle Time is the fastest cycle time that your process can achieve in optimal circumstances. Therefore, when it is multiplied by Total Count the result is Net Run Time (the fastest possible time to manufacture the parts).

Since rate is the reciprocal of time, Performance can also be calculated as:

Performance = (Total Count / Run Time) / Ideal Run Rate

Performance should never be greater than 100%. If it is, that usually indicates that Ideal Cycle Time is set incorrectly (it is too high).

Quality

Quality takes into account manufactured parts that do not meet quality standards, including parts that need rework. Remember, OEE Quality is similar to First Pass Yield, in that it defines Good Parts as parts that successfully pass through the manufacturing process the first time without needing any rework.

Quality is calculated as:

Quality = Good Count / Total Count

This is the same as taking the ratio of Fully Productive Time (only Good Parts manufactured as fast as possible with no Stop Time) to Net Run Time (all parts manufactured as fast as possible with no stop time).

OEE

OEE takes into account all losses, resulting in a measure of truly productive manufacturing time. It is calculated as:

OEE = Availability × Performance × Quality

If the equations for AvailabilityPerformance, and Quality are substituted in the above and reduced to their simplest terms the result is:

OEE = (Good Count × Ideal Cycle Time) / Planned Production Time

This is the “simplest” OEE calculation described earlier. And, as described earlier, multiplying Good Count by Ideal Cycle Time results in Fully Productive Time (manufacturing only Good Parts, as fast as possible, with no Stop Time).

Why the Preferred OEE Calculation?

OEE scores provide a very valuable insight – an accurate picture of how effectively your manufacturing process is running. And, it makes it easy to track improvements in that process over time.

What your OEE score doesn’t provide is any insights as to the underlying causes of lost productivity. This is the role of AvailabilityPerformance, and Quality.

In the preferred calculation you get the best of both worlds. A single number that captures how well you are doing (OEE) and three numbers that capture the fundamental nature of your losses (Availability, Performance, and Quality).

Here is an interesting example. Look at the following OEE data for two sequential weeks.

OEE Factor Week 1 Week 2
OEE 85.1% 85.7%
Availability 90.0% 95.0%
Performance 95.0% 95.0%
Quality 99.5% 95.0%

OEE is improving. Great job! Or is it? Dig a little deeper and the picture is less clear. Most companies would not want to increase Availability by 5.0% at the expense of decreasing Quality by 4.5%.

CALCULATION EXAMPLE

Now let’s work through a complete example using the preferred OEE calculation. Here is data recorded for the first shift:

Item Data
Shift Length 8 hours (480 minutes)
Breaks (2) 15 minute and (1) 30 minute
Downtime 47 minutes
Ideal Cycle Time 1.0 seconds
Total Count 19,271 widgets
Reject Count 423 widgets

Planned Production Time

As described in the OEE Factors page, the OEE calculation begins with Planned Production Time. So first, exclude any Shift Time where there is no intention of running production (typically Breaks).

Formula: Shift Length − Breaks

Example: 480 minutes − 60 minutes = 420 minutes

Run Time

The next step is to calculate the amount of time that production was actually running (was not stopped). Remember that Stop Time should include both Unplanned Stops (e.g., Breakdowns) or Planned Stops (e.g., Changeovers). Both provide opportunities for improvement.

Formula: Planned Production Time − Stop Time

Example: 420 minutes − 47 minutes = 373 minutes

Good Count

If you do not directly track Good Count, it also needs to be calculated.

Formula: Total Count − Reject Count

Example: 19,271 widgets − 423 widgets = 18,848 widgets

Availability

Availability is the first of the three OEE factors to be calculated. It accounts for when the process is not running (both Unplanned Stops and Planned Stops).

Formula: Run Time / Planned Production Time

Example: 373 minutes / 420 minutes = 0.8881 (88.81%)

Performance

Performance is the second of the three OEE factors to be calculated. It accounts for when the process is running slower than its theoretical top speed (both Small Stops and Slow Cycles).

Formula: (Ideal Cycle Time × Total Count) / Run Time

Example: (1.0 seconds × 19,271 widgets) / (373 minutes × 60 seconds) = 0.8611 (86.11%)

Performance can also be calculated based on Ideal Run Rate. The equivalent Ideal Run Rate in our example is 60 parts per minute.

Formula: (Total Count / Run Time) / Ideal Run Rate

Example: (19,271 widgets / 373 minutes) / 60 parts per minute = 0.8611 (86.11%)

Quality

Quality is the third of the three OEE factors to be calculated. It accounts for manufactured parts that do not meet quality standards.

Formula: Good Count / Total Count

Example: 18,848 widgets / 19,271 widgets = 0.9780 (97.80%)

OEE

Finally, OEE is calculated by multiplying the three OEE factors.

Formula: Availability × Performance × Quality

Example: 0.8881 × 0.8611 × 0.9780 = 0.7479 (74.79%)

OEE can also be calculated using the simple calculation.

Formula: (Good Count × Ideal Cycle Time) / Planned Production Time

Example: (18,848 widgets × 1.0 seconds) / (420 minutes × 60 seconds) = 0.7479 (74.79%)

The result is the same in both cases. The OEE for this shift is 74.79%.

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Increase Worker’s Efficiency https://thinkstudio.in/increase-workers-efficiency/ https://thinkstudio.in/increase-workers-efficiency/#respond Thu, 12 Mar 2020 10:33:56 +0000 https://thinkstudio.in/?p=211875 Indian manufacturing sector depends on hiring casual workers for its production planning. However, we all know that contract or casual workers have some issues which is a routine problem for all of us. In order to solve this challenge, we used AI to raise warning in case your worker is performing at a speed less […]

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Indian manufacturing sector depends on hiring casual workers for its production planning. However, we all know that contract or casual workers have some issues which is a routine problem for all of us.

In order to solve this challenge, we used AI to raise warning in case your worker is performing at a speed less than required. such interventions can automate your production , best part is this software can work even for packaging, labelling, packing, whatever be the task of your workers, we can analyse their rate of doing it and present the same to you in easy to use excel format.

We think production needs instant action, so instead of waiting for production manager to give caution to workers , our voice enabled software can give advice/ cautions to workers instantly , this system instills the belief in workers that they are being watched and reduces following issues of:

  1. Slow rate of work
  2. idle gossips on shop floor
  3. frequent breaks
  4. theft cases are reduced as they now know that intelligent system is catching their hand movements
  5. Floor supervisor gets more time to focus on quality and other activities rather than focusing on time keeping.

Product is robust and can perform in all conditions and temperature, comes with full warranty for 1 year.

For Demo you may contact : Sanjeev Sharma ( Our Authorised Dealer for Uttrakhand) at +91-6399935149

Authorised Dealer
HS Enterprises, Haridwar

 

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Assembly Line Manager by TDI https://thinkstudio.in/assembly-line-manager-by-tdi/ https://thinkstudio.in/assembly-line-manager-by-tdi/#respond Thu, 12 Mar 2020 10:11:27 +0000 https://thinkstudio.in/?p=211872 ALM or Assembly Line Manager is designed to help manufacturers achieve the following objectives : 1- Know who is efficient worker/workers in your plant 2- Helps in production planning and forecasting 3- Reducing your machine running time, thereby saving maintenance cost 4- Helps in optimizing production cost 5- Screen or allocate resources to various assembly […]

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ALM or Assembly Line Manager is designed to help manufacturers achieve the following objectives :

1- Know who is efficient worker/workers in your plant

2- Helps in production planning and forecasting

3- Reducing your machine running time, thereby saving maintenance cost

4- Helps in optimizing production cost

5- Screen or allocate resources to various assembly line set up by using benchmark set by you or by intelligent analytics in ALM.

6- Leads to great reduction in overtime and this saves lot of cost.

ALM – is based on scientific concept of time and motion study used by most big corporations, however due to such software being very costly most MSME are not able to use such tools , but TDI has used advanced VIDEO ANALYTICS along with ANOMALY DETECTION algorithms to arrive at best results.

It comes with very easy to use and intuitive interface and can update management in real time about various key metrics like:

1- Do we need to increase or decrease assembly line speed.

2- Historical trends of efficiency

3- Day end projected production numbers.

4- Your entire working staff gets ranked automatically as low, medium and high efficiency bucket , which may help in mix and match strategy.

For Demo you may contact us at 9568924536

 

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