Tech Beyond the Myth 01

Dissecting what drives technology today.

Experiments

Creating a Forensics Report

For a damaged and ultimately defect Hitachi TV, the journey ended on our 'dissecting table' when we disassembled the device in order to create a forensics report. This report stated the methodology, the individual components found and finally the damage suspected to be linked to the TVs demise. Below, some impressions of the process can be found as well as the link to the report itself.

Our proud group presenting the (at the time) still assembled TV.

Disassembling the TV (from top left to bottom right: Lifting the LCD screen off the backlight panel, an overview of the components found (with the power supply board on the far right), a close-up of a missing HDMI port, a microscopic view of the LCD panel showing the RGB diodes forming each pixel.

A flat lay of the individual components found.

Forensic Report: Hitachi TV VES650QNTS-2D-N41

Identity of the reporting agency MDEF
Case identifier Forensics of the Obsolescence
Identity of the submitter Guillem Comprodon
Date of receipt 09/11/2021
Date of report 09/11/2021
Identity and signature of the examiner Paula, Ruben, José, Julia, Chris

Key Data

Brand: Hitachi
Model: VES650QNTS-2D-N41
Manufactoring Number: V20B00537
Manufactured by: Vestel
Color: black
Assemblied in: Turkey
Tested: CE (self-certification)
Size: 65"


Forensic Questions

What does it do?

Displaying images and video on a 65" screen via analog (RCA) and digital input ports (VGA, HDMI, USB, Ethernet and Coax) with audio (3,5mm jack) support.

How does it work?

User connects the desired medium to the corresponding input-port and navigates to the input signal on the television’s menu. The ‘input-PCB’ translates these signals to visual output on the LCD-screen being backlit by the LED lightbox.

How it’s built?

Why it failed, or it wasn’t used anymore?

Cracked LCD-screen.

Steps taken

  1. Disassembly
  2. Component mapping
  3. Circuit mapping
  4. Testing backlighting (isolated)

Results

How many motors we find inside, does it contain a computer or microcontroller?

  • Several types and sizes of capacitors.
  • Large 2GB RAM on controlling PCB unit.
  • Microcontroller cooled by aluminum profile.

Did the appliance fail, why?

Yes, incorrect visual output. Cracked screen with only a part of the tv’s side-menu showing.

Conclusions

  • Fab for Economics vs Fab for Environment:
    The traditional mindset about the economic model makes the “cost/benefit” the main purpose of the industry, leaving long term purposes (environment contamination, carbon footprint, recycling and reutilization) aside. The challenge for this type of products is to start producing in a circular economic way.

  • Black Box (TV) has inside black boxes that have inside blackboxes that have inside blackboxes:
    The understanding about machines that are made of smaller machines, each one with their own utility, is a interesting fact when fixing or reinventing products. In the case of this TV, we had a lot of black boxes that could be used for fabrication of other type of products.

  • The difficulty of disassembling it without breaking it:
    Disposable products, not made for fixing at home, is a paradigm that is changing. In today´s world the concept of DIY is attached to the way humans and things are related.

  • The industry managed to settle products for different public using the same boards:
    Low cost and simplificity for production is exemplified, fabricating different models for different public using the same “materials”.

  • It’s not that the TV did not work, it was only the the black LCD screen:
    Can the client replace the screen?, or is too dangerous?, or is not favorable for the industry?

Reflections

Questioning what is inside the products we use on daily base provided insights on how extremely extensive modern day production systems are. Supply chains literally stretch across the globe with one product having components being manufactured in Japan, Turkey, Russia, China and Taiwan. And more so, each of these locations having it’s own selection of suppliers with sub-components, sub-sub-components and raw materials that can come from e.g. Africa, South-East Asia or South-America. With likeliness of being cross-distributed between them so that any product produced by this system - on itself - has travelled an insane amount of distance and, in a way, is an encapsulement of the world’s efforts itself. 🌍

Aside of that we learned that by disassembling a recent model HITACHI television 📺 and web-researching the parts inside that the same PCB (printed circuit board) produced by a single chip-giant can be sold to several (direct market-rivals) electronics-companies and they can sell it to different customer segments by choosing to in- or exclude certain functionalities on the same single PCB. In the case of our HITACHI tv this was shown as the unused outlines of where an HDMI-port would be in a more expensive model of the same brand.

I think that for those willing to see it’s clear as day that this one-way-stream system cannot survive longterm and exploits its early layers for the benefits of those at the end.
Yes, the consumer has his television and he has it cheap, but at what cost for those that mined its materials and what purpose will it serve next.

Our television got to us because its LCD screen was cracked. The LCD screen, just one broken component out of at least ten perfect working parts and still the entirity of the product was discarded. Even with the knowledgement of which component being the infunctional one, since it gave this as visual feedback on the screen.

Uncovered Supply Chain


https://www.statista.com/statistics/270277/mining-of-rare-earths-by-country/

The same Forensic Report can be found on HackMD as well

Data Gathering Exercise

We decided which categories to research, deciding on finding out if the ingredients within IAAC’s specific vending machine were local. We started small, then built up until we reached a global scale of interconnected supply chains. The detailed methodology and results can be seen below.

Our question and hypothesis finding process.

From the top left: The object of desire (a sandwich form the local vending machine, Oscar teaching Python fundamentals, employing Python web scraping scripts and visualizing the location producers of readymade sandwiches across western Europe.

Journal: Local Foods

MDEF: Measuring the world / A world in data activity report.

A report by: Angel Cho, Chris Ernst, Julia Steketee, Paula Del Rio, Tattiana Butts and Vikrant Mishra.

Journal Index

From objectives to the hypothesis

Brainstorming

Project Goals

Objective:
We want to eat more locally produced food.

Question:
Where does our food come from?

Hypothesis:
the majority of food in the vending machine is not locally produced.

Tips

Explain one or more mistakes you’ve done during that phase?
What would you change if will do it again?

Our expectations were too high: we assumed that a lot of the data regarding food production would be available to the public.
Maybe we could re-orient our objective from location to nutrition.

From hypothesis to data

Tools selection

Post multiple images about the tool. What tool did you use? Would you choose a different tool now?

Web scraping: Manually and Automated through python

Finding websites that have databases about food production, import and export

Oec

ITC Trade Map

Tool usage documentation

How can others replicate your data capturing process again?

They can find the base code of our web scraping tool on the FabLab hackmd ( Here.)

All database sources are written below.

Data capturing strategy

How do you combine the tool provided with your creativity to prove your hypothesis? How long did you capture data?

We decided which categories to research, basing ourselves on the ingredients within IAAC’s specific vending machine. We started small, then built up until we reached a global scale of interconnected supply chains.

Materials needed

List all the materials needed, including those given to you, those you source or even things you built yourself.

Techniques used:

  • Manual “web scraping”
  • Automated web scraping
  • Scanning products through Open Food Facts app
  • Researching through food brand website

Resources used:

Detail setup instructions

Explain the setup process. You can simply publish multiple images about your setup.

Map of our process:

Data collected

Describe the raw data you collected by posting a sample i.e. a picture, a screen capture, etc.

Excel sheets generated from open food facts:

Map from open food facts

Excel sheet from ITC trade map

via GIPHY

Interactive map from OEC

Interactive map from CIAT

Thanks to all of these sources, we managed to cross reference the information which we obtained. We noticed many differences from one resource to the other.

Data capture

Data summary

Data Summary
Project Title Food Origins
Capture Start 11-11-2021
Capture End 12-11-2021
Original Data Format Website html
Submitted format CSV file
Total Data Points approximately 5000
Number of datasets 5 seperate files
Data Repository https://github.com/fablabbcn/mdef-a-world-in-data

Data insights

Post at least two images of a chart, a screen-shoot of your data, that you used to prove if your hypothesis is false.

We were surprised to see that the Natwins cookies claimed their product was “local”. However, they do not define what exactly local means, and later state that their ingredients come from the “Mediterranean”.
The mediterranean area includes 21 countries, which means that the food origins are almost untraceable (Albania, Algeria, Bosnia and Herzegovina, Croatia, Cyprus, Egypt, France, Greece, Israel, Italy, Lebanon, Libya, Malta, Monaco, Montenegro, Morocco, Slovenia, Spain, Syria, Tunisia, and Turkey)

We decided to buy a sandwich from the vending machine and trace the possible origins of the main ingredients, using OEC’s data concerning Spain’s imported products.
The unit of measurement was the value of product in USD$ and not in tonnes.

The primary ingredients of the sandwich were:

  • wheat
  • pig meat
  • cheese
  • nuts
  • eggs
  • yeast
  • olive oil

And these were the primary imports in Spain:

via GIPHY

Of course, this only displays the probability of where each component originated if they were imported.

Web scraping v/s Open APIs

Sometimes it might be beneficial to see if there is an open API to access a database instead of going for web scraping the frontend data right away. In the case of Openfoodfacts.com, they offered an open and very well-documented API, offering various export formats. This allowed us to easily download and analyze the complete dataset for the product category of ‘sandwiches’. This was made possible thanks to all the data being covered by the Open Data Commons License.

Conclusions

It is very difficult to retrieve information about where food comes and goes
There is a lack of transparency regarding the movement of goods
There is no detailed information available to the public about food sources
Recognising that Web Scraping is an option, but not always the best or more efficient one.

Tips

Explain one or more mistakes you’ve done during that phase? What would you change if will do it again? What if you will have more time? (max 560 char)

Defining a more specific target in our hypothesis, would have allowed us to access more relevant information.

Possibly using a different context (restaurant, grocery store) would have yielded more interesting results.

Find the full group presentation here

Activity conducted by Angel Cho, Chris Ernst, Julia Steketee, Tattiana Butts, Paula Del Rio and Vikrant Mishra.

The same Data Gathering Report can be found on HackMD as well

Useful links / For further reading

Smart Citizen Kit (Citizen Science Station)
Salus Coop (Citizen Science Database)
Beautiful Soup 4 Web Scraping Tool (Technical Documentation)
Zenodo (Open Science Platform)
iFixit (Self-Repair Ressources)

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