Bene Bono's Warehouse Production Line: Web Technologies Meet Industrial Sensors
Summary
TLDRこのスクリプトは、Bonuというフランスの会社が、食品ロスを減らすために不規則な形や色の果物や野菜を販売するビジネスモデルと、その生産ラインの最適化について説明しています。Bonuは、顧客がオンラインで注文をカスタマイズできるフルカスタマイズ機能を提供し、生産性向上とエラーの減少を目指して、新しいセンサー技術を導入しました。このイノベーションにより、Bonuはより効率的で信頼性の高いサービスを提供し、将来的にはデータ利活用とより多くの機能拡張を計画しています。
Takeaways
- 📈 会社のミッションは、食品ロスから良い製品(果物や野菜)を救うことです。
- 🥦 販売している商品は、通常の店では販売されないが、理由があって販売されない商品も含まれています。
- 📊 3年間の運用により、フランスとスペインの6つの主要都市に存在し、2万以上の顧客を有しています。
- 🚀 週に1万を超える注文を準備し、最大の倉庫でその数は数ヶ月以内に倍増する予定です。
- 🛠️ 現在の生産システムはシンプルで効率的ですが、よりカスタマイズされた注文に対応できないため、改善が必要とされています。
- 🔄 新しい生産ラインには、紙レスで、従業員のトレーニングが不要、果物や野菜のリストが変わると自動的に対応できるシステムが採用されています。
- 🔧 技術的な選択においては、ロックインされていない高度に信頼性のあるシステムを追求し、技術チームのスキルを最大限に活用することを目指しています。
- 🌐 産業用センサーを使用しつつ、オープンのEthernet/IPプロトコルを利用することで、プロペティのハードウェアから離れています。
- 📱 従業員用のスクリーンは、消費者向けのタブレットで、従業員が簡単に注文を準備できるようになっています。
- 🔄 部署には多くのスクリーンがあり、生産ライン上の各ステーションで何が起こっているかをリアルタイムで確認できます。
- 🔍 データの利活用により、マージン計算や納品チームの選択肢に役立つ情報を得ることができます。
- 🚧 今後の課題としては、より高い信頼性を確保し、アプリのバージョンアップや監視システムの改善が挙げられます。
Q & A
Bonuのミッションは何ですか?
-Bonuのミッションは、食品ロスを減らすことです。具体的には、通常の店では販売されない理由がある果物や野菜をセーブし、それらを消費者に届けることです。
Bonuが提供する商品はどのようなものですか?
-Bonuは果物や野菜を始めとして、一年半後の現在では食品用品や卫生・家事用品、ペットフードまで展開しています。これらの商品は通常の店では販売されないが、品質には問題がありません。
Bonuの配達システムはどのように動作しますか?
-Bonuはサブスクリプションモデルを採用しており、顧客は毎週の注文を準備し、直接消費者に商品を販売しています。また、フルカスタマイズ可能な注文システムを導入し、顧客は毎週の提供商品から自分の注文を完全にカスタマイズすることができます。
Bonuの生産システムの課題は何でしたか?
-Bonuの生産システムは非常に基本的で、デジタルツールがありませんでした。従業員は注文準備中に紙のリストを読み、注文の準備を行っていました。しかし、注文の量が増加し、よりカスタマイズされた注文に対応するためには、現在のシステムの改善が必要でした。
新しい生産システムの設計原則は何でしたか?
-新しい生産システムの設計原則は、紙レスで、新入社員のトレーニングが不要、果物や野菜の販売リストが変わることに対応できること、そして、新しい技術を導入するための大きなCAPEXコストがなくなるように、技術を選択することが重要でした。
Bonuが選んだ技術はどのようなものでしょうか?
-Bonuは、Go言語を使用したバックエンド技術、Reactを使用したアプリケーション開発、そしてIndustrial sensorsを使用しました。また、消費者向けのタブレットを使用し、産業用SENSORと接続することで、より柔軟で信頼性の高いシステムを実現しました。
新しい生産システムの利点は何ですか?
-新しい生産システムは、従業員が注文を準備する際に紙のリストを読む必要がなく、タブレット上での直感的なインターフェースを使用できるため、より迅速で正確な作業が可能になります。また、システムのカスタマイズ性や柔軟性が高まり、生産ラインの改善や新しいサービスの導入が容易になります。
新しい生産システムの導入に直面した課題は何でしたか?
-新しい生産システムの導入に直面した課題には、適切なセンサーの選定、APIの遅延、常にオンのスクリーンの管理などが含まれます。特に、センサーの選定では、高品質で安価な製品を見つけることが難しく、APIの遅延は画面の即時反映に影響を与え、スクリーンの管理ではMDMソフトウェアの複雑さとHTTPS接続の課題が必要に対応する必要がありました。
Bonuは今後どのような方向性を進める予定ですか?
-Bonuは、生産ラインで収集されたデータを活用し、マージンの計算や購入チームの選択肢の最適化などに役立てることを目指しています。また、システムの信頼性を向上させるために、センサーの交換を迅速に行えるようにし、アプリのバージョンアップを自動化することも計画されています。
Bonuのフルカスタマイズ可能な注文システムはどのようなものですか?
-Bonuのフルカスタマイズ可能な注文システムは、顧客が毎週提供される商品から自分の注文を完全にカスタマイズできるシステムです。顧客は木曜日に通知を受け取り、その中で注文をカスタマイズすることができます。そして、月曜日から注文が準備され、顧客に発送されます。
Bonuのサブスクリプションモデルの具体的な動作方法是どのようなですか?
-Bonuのサブスクリプションモデルでは、顧客は毎週の注文を準備し、選択した商品が毎週配送されます。顧客はサブスクリプションにコミットする必要はありません。毎週、顧客は受け取るバスケットを選択し、スキップすることも可能です。また、いつでもサブスクリプションを一時停止することができます。
Outlines
📣 導入と現状の説明
MarkがCTOとして、Bonuの最後のトークでピッキング構造とプロセスの最適化について話す。Bonuは、食品ロスから良い製品を救うというミッションを持つフランスの会社。彼らは新しい生産ラインを設計し、デプロイする際に直面した課題について説明する。
🚀 新しい生産ラインの課題と改善
Markは、新しい生産ラインの課題について説明し、よりカスタマイズされた注文に対応する必要性とそれに伴う生産性の向上、製品のトレース性、エラーの低減が求められることについて話す。また、システムの設計原則として、紙レス、トレーニング不要、果物や野菜のリストの変更への適応性、低コストのテクノロジー選択を重視した理由も説明する。
🔄 技術的な取り組みと生産ラインのアーキテクチャ
Markは、産業用センサーから見かけないプロペティを除く方法を探求し、オープンプロトコルを使用するセンサーを見つけたことを説明する。彼は、生産ラインのシンプルなアーキテクチャと、GoとReactを使用して開発されたバックエンドエンジン、およびプロダクトラインに接続されたコマースプラットフォームについても話す。
🎥 生産ラインの実際の運用と改善点
Markは、生産ラインの実際の運用方法と、リアルタイムでのセンサーイベント記録による分析、そしてUXの改善について説明する。また、センサーの選択、APIの遅延、デプロイメントの複雑さなどの課題と、それらに対処する方法についても話す。
📈 次のステップとデータの活用
Markは、生産ラインのデータを活用してマージンを計算し、購入チームの選択を支援する計画を説明する。また、システムの信頼性の向上、アプリのバージョン管理、およびシステム全体の監視の強化が今後の課題となると話す。
🗓 プロジェクトの開発期間と費用
Markは、プロジェクトの設計開始からセンサーの発見まで1年かかりました。開発期間はQ1からQ3までで、センサー1個あたりの費用は約600ユーロと述べる。また、生産ライン上の従業員数と、その効率についても話す。
🚚 出荷プロセスと今後の展開
Markは、入荷プロセスの効率性と、出荷時に使用される特殊なアプリケーションについて説明する。彼は、日々の注文数と、アプリケーションのストレステストについても話す。さらに、Bonuが販売する商品の特徴と、将来的にアプリやバックエンドに追加したい機能についても触れる。
🙌 終わりの致し方
トークの最後に、Markが参加者に対して感謝の言葉を述べ、質問があれば呼びかけることを忘れずに述べる。
Mindmap
Keywords
💡production line
💡sensors
💡customization
💡barcode scanning
💡e-commerce platform
💡real-time data
💡traceability
💡digital tools
💡subscription model
💡customer experience
Highlights
Introduction to the new production line and its challenges in designing and deploying the system.
The average time spent on grocery shopping is 60 to 90 minutes, while warehouses have to prepare an order every 10 seconds.
Bonu's mission is to save good products from waste, focusing on fruits and vegetables that are considered imperfect but still perfectly good.
Bonu started selling grocery products and expanded to hygiene, housekeeping products, and pet food.
The company operates on a subscription model, selling directly to consumers in France and Spain.
Bonu's largest warehouse near Paris prepares over 10,000 weekly orders, a number expected to double in the next few months.
The old production system was basic and efficient but lacked digital tools, leading to the need for a new system to handle increased order volumes.
The new system aims for higher productivity, better traceability, and less error-prone order fulfillment.
The design principles for the new system include being paperless, requiring no training, and adapting to changing lists of fruits and vegetables.
Technology choices for the new system prioritize reliability, adaptability, and leveraging existing skills within the tech team.
The new production line uses an engine based on Go, the same technology used for Bonu's e-commerce platform.
The production line includes sensors, a conveyor belt, and tablets displaying what products to put in each order.
The system allows for full customization of orders, a shift from a standardized selection of fruits and vegetables to a completely personalized order.
Challenges faced during the development included the choice of sensors, network and API latency, and managing always-on screens.
The new system records every sensor event, providing data on handling times for different products, which can help calculate margins and inform purchasing decisions.
The development of the new production line started a year ago, with a focus on launching the full customization offer in Q4 of the current year.
The cost of one sensor is around 600, with additional expenses for wiring and electrical work.
The production line can handle more than 2,000 orders per day, with the main operational limit being the pace of refilling the line and the number of employees.
Bonu sells products that cannot be sold in regular shops due to appearance or size, not because of regulations.
The company operates on a subscription model with no commitment, allowing customers to choose their orders weekly and add extra items as needed.
Transcripts
hi everyone um so welcome to our next
and final talk um I'm have to welcome
Mark you CTO at B AO um and you us about
something about um basically um
optimizing your picking structure your
picking process exactly um yeah and uh
this is then I would like to hand over
to you and uh yeah us tell us a bit
about what you do with sensors and stuff
thank you very much hello everyone so
I'm Mark I'm been you I'm super happy to
be here today to talk to you about our
new production line and explain a little
bit the challenges we we face when
designing and deploying that new system
and I thought with a very simple
question how much time do you guys spend
winkly on grocery shopping and the
answer to that question is roughly 60 to
90 minutes just to fill your baskets on
average
uh depending on the like Europe
countries and unfortunately we have like
uh much less time to uh fully order at
the warehouse and we have to uh prepare
an order roughly every 10 seconds uh at
the warehouse and this number is going
uh has to go down like quite a lot in
the next few uh months because our
volume of order is like going up thanks
to
that uh and so we had a we have a lot of
improvements to do to our own current
production system but let me give you a
little bit of context about uh bonu so
bonu is so it's a French established
company and our mission is to save good
products uh from waste and by good
products I mean fruits and vegetables
which are the the main uh products are
the main product that we we sell we
started with them uh then after a year
and a half we started selling grocery
products and now we also have like
hygiene and housekeeping products and
also pet food and all these products
that we sell uh are s because they
wouldn't have been sold in a regular
shops for many different reasons for
example uh concerning uh foods and
vegetables you see shaping carrot here
yeah most of our uh TR vegetables are
sold on V because they have the wrong
caliber or wrong shape or wrong color
you name it but they are perfectly uh
good products and same goes with like
Grocery and other kind of prod save they
are like some C with reason so that they
cannot be sold in regular shops so we
buy them directly from producers and
sell them to a subscription uh uh plan
to our customer so we sell directly to
consumers in France and Spain so so we
launched three years ago we are present
in six major French cities and think
five sorry five major Spanish cities we
have over 20,000
customers um and we prepare more than
10,000 weekly orders in our largest
Warehouse which is nor near near Paris
and uh that number that number is like
super to double in the next few months
the number of orders we prepare in our
largest warehouse and that's why we have
to add to our production system uh so
that's our current like it's the old
production system that we had before the
current project so it's a very basic one
but quite efficient I mean is no uh
digit digital tool at all uh basically
you have both the customers all in the
conveyor belt here uh all the fruit and
vegetables are just behind on the orange
shelves and here you got a a sheet of
paper close that's the sheet of paper
that indicates what's going to be put in
the in the baskets that's the order
content and I took an example of well
the highest complexity that we may have
with the current system so customer has
like some potato carrots didn't want
cucumber so they remove this one replace
by sweet potatoes and you have two kinds
of grocery products pasta on honey um
and that's the most complex order we can
do now like you can replace one fruit or
or one vegetable and that's it uh more
customization would be like too complex
with that system because the employees
have to read uh the paper during the
order preparation and if the orders are
too different from one another it's like
too complex and we would we have a lot
of uh errors in the order
fulfillment
um so we have uh two new uh constraints
uh that will put pressure on that system
first one is we have like higher volumes
we we have a lot of like new customers
that we gain every week so we have a few
more thousand orders per week in that
that warehouse before the end of the
year um and we hope also have a new
offer that we would like to launch uh
that we will launch in October uh
actually we launch today the offer for
the the employees so that's really the
launch of that project uh and it's going
to be like public for the like regular
cers starting in two weeks and that's
what we call the full customization that
means we're going to shift from a system
when you have a selection of fruits and
vegetables which are almost the same for
everyone to a system you can completely
customize your order based on the
product we will have both for that
specific week that means on Thursday
you're going to have a notification
these are the products that are
available like for you to order you have
like two to three days three days
actually to customize your order and
then uh we prepare the order starting on
the Monday and ship to customers um but
that means when we will have launch that
offer every order is going to be
different and we cannot rely on the
current prediction system to uh F all
the orders the new uh requirements on
the system are a higher productivity
because we have to go from like $10,000
per week to probably the double in that
warehouse only um we have to have a DAT
tracability of the which product we we
sell to each customers because with
higher volumes we have like several
producers for only apples for example
only carrots you have to know with what
carrots did you have in orders for like
for
reason uh and we have to have a system
which is like less error
prone uh to cope with the complexity of
the orders so the design principles that
we had for that project is uh the system
shouldn't be paper based uh so that uh
the employees don't have to like read
the order to read sheet of paper to by
the order um the system shouldn't
require any training uh because we have
a lot of like new employees is coming
every week and that should be like able
to prepare an order like immediately or
after a few minutes of training not more
than that and the system should adapt
itself to a changing list of fruits and
vegetables we sell different fruits and
vegetables every day and we have to
reconfigure the production line uh
probably every day also um and also we
should be able to deploy that produ
neware houses without huge capex uh cost
and that means we have to be like uh
very careful the choice of technology
that we're going to deploy so we have
three um principles for the tech choices
we make um the first one is we didn't
want any V lock uh because we want to be
able to adapt the system completely to
the way we prepare orders or to uh the
offer we make we make to our customers
or our warehouse trategy or you name it
so we going to be like super uh capable
of adapt the system and change it
um we wanted to have like a super
reliable system because we are talking
about production and all incidence are
like super expensive it could stop the
production light so we're GNA like favor
boring Tech to compared to F Tech um and
the last principle is we
also uh wanted
to um
maximize the the use of the skills will
have in the tech team and not having
having to learn like new languages or
new technologies or new platforms so
that means less Tech better than more
Tech uh and try to keep our Tech stch as
rational as
possible so that being said if you look
at the
classic architecture of a production
line uh in a factory or in a warehouse
usually you have like industrial
senses uh which communicate with an
automation system using a an industrial
bus for example modbus which is the one
of the most
well-known uh the automation system is
like usually proprietary uh and then the
automation system displays informations
on on screens R screens uh using also
some kind of prary protocol and this
system communicates with either ANP or
eCommerce platform to be link to your
with your business and for
example what sorry I click on stop y
yeah so some example of a production
line is like this one that's a big to
light system pretty common in e-commerce
companies for example uh that this has a
lot of proprietary hardware and a lot of
proprietary systems not specifically
what we wanted uh so we thought about
how we could get of the proprietary part
of that
architecture um and the thing is so
industrial
senses there are I mean there's no way
you can avoid them you need reliability
you need to have for example high
frequencies point scannings or you need
to have like super reliable systems so
there's no way you can avoid that but
the others we thought maybe we could
like replace the automation set with a
regular uh server that we could develop
using same Tech that we use for our web
servers our API servers and also for the
uh rug screens the public replace them
with consumer tablets uh and develop uh
like a human interface on this tablet
using classical mobile tech um but the
issue now is how we can connect to the
industrial sensors uh and we had to find
sensors that don't use like proprietary
or industrial protocol but regular cpip
protocols uh more on that later but we
were able to find them and we had a
super well think simple architecture for
our production line basically we use an
engine which is based on goong which is
our backend technology that we use for
our e-commerce platform with same
developers who can work on our
e-commerce platform or uh at the
warehouse on our production line
engine um we the that engine connects so
to the Commerce platform and server that
we made to configure that Prof l so all
are based on the same uh technology
that's goong and SQL and that's it um
and
the applications we developed uh on the
production line is using react GS that's
the same Tech that we use on our
consumer app and also they have those
industrial back
region that's the complete setup that
we' made uh you've got the conveyor
built uh that you've seen uh sooner
that's exactly the same it hasn't
changed we added some sensors that you
can see in green uh you still have the
orange shelf and vegetables on the top
got tablets that indicates what product
you should put in each order uh was like
looks like looks pretty easy uh but
let's show it in live let's slides and
more
videos so that's the first uh that's the
beginning of the prodction line uh
what's new with that prod line is we
need to uh generate a label that we can
to stick on the on
the the baskets and the all the baskets
going be put in large plastic box which
are easy to roll on the conveyor and
which are easy to be scanned by the
sensors so first thing is we're going to
put the on the table print the
label and that's going to be the south
of the jary of that box so we put here
up it's scan and you have like
automatically delay all that that it's
magic that's all the label so in each
box you're going to have three customers
orders and then that's
the that's real work when we are on the
production line
so youve got
the it goes so you slide the box here
and you see it changes immediately on
the screen on top we're going to do it
again uh and you've seen all the red
lights
here sens put on
the so that's the prediction line at
work
and that's what's displayed on the
screen that's a react basic react app
that we deployed and it's what's nice
with that approach is super easy to
change the ux and deploy it remotly uh
if we have like I don't know people that
have issues know with the colors of the
displays uh so that their work is easier
um so here you've got the three orders
which are in the bag uh in in the Box
sorry and here for for example this
order we got four different fruits and
vegetables which are possible so each
employee can manage four different
fruits and and vegetables and these are
the places on the shelves in front of
him but that means here for that order
have to take four bags on the left
bottom shelves two two bags on the right
bottom shelves and two on the top shelf
and nothing from the vbl it's super easy
I mean you you could already come to our
house and pick orders you know how it
works that that's was the the aim and
the color
corresponds to the quantity uh for
example uh the cauliflowers it's red
because it's double there are two pieces
the walnuts they're coming like two bags
together here we've got the double St
spread so really it's super easy to uh
know what you should put in each order
um and that's the employee screen
and that's just to show you what's going
to happen uh under the hood so on the
left you're going to have an employee
screen which is on the second station of
the production L not the first one
that's second just show you and here
you've got the dashboard which is
display in the warehouse shows what's
happening on the production
line so we're going to like simulate
this fact that we put the Box on the on
the position line so it will appear over
here on B1 the first station then move
on B2 it's going to appear appear on the
left screen it's second screen okay now
it starts the Box arrive here on B1 and
you're going to see here we have two
2,000 orders to prepare and it's going
to change to one that's the first order
got the three order numbers and the
content here now we move to be to that's
new screen for the second stage and then
another box and there it goes that's the
life of prodiction line so you can see
uh remotely what's happening on the
prodiction line a very nice tool to uh
to manage also remotely what's happening
what do in the
warehouse this is done in react also
super easy to uh change and to
redeploy
and these are the two last videos I
actually uh colleague of mine sent me
those videos just like an hour ago
because today is the day which we
launched that production line actually
so it's really dday for Ben Bono and I'm
not here I'm like I'm hidden in Berlin
where the team is like launching
everything um so that's the production L
really is the first orders we have
prepared today
that system you see the three orders in
each B in each box uh on the screen on
top uh very short videos and the second
one you see a little bit more what's
happening so we put the baskets in the
box that's what we saw that's a complete
view of the production lines with all
the screens which are being used right
now so there are up to 13
screens that mean certain employees and
so what what did we what what challenges
did we face and what lessons did we
learn during that
joury uh the first challenge was uh the
choice of sensus and it was like quite
difficult to find the right one the
criteria where
where like industrial performance that
means
highest barcode scanning and a high
frequency that system is like super
reliable and uh and that you have like
instant change when you put the Box on
the sensor um we needed an EET
connection on the full cpip
compatibility and an afford a affordable
price and that is like super difficult I
mean industrial sensors usually are not
uh fully ethernet compatible I mean untr
level ones uh so we are talking about
highend senses which may be super
expensive so we were able to find like
sense from Kon the Japanese manufacturer
which were like in our price range but
that was really a major major issue at
the beginning of the project um Second
Challenge was uh Network on API latency
is really really matter if you want to
have like an instant change of the
screen
and while talking about like a
production line where the the
productivity you want is like very high
there is no way you can like wait half
of a second or even a quarter of a
seconds of the display on the screens
but that means all the other contents is
stored locally in the production L
engine so we have to synchronize and
that actually adds quite a lot of
complexity on the project uh because the
the production engine synchronizes
itself with the e-commerce platform that
when you scan a box I mean the auto
content is already there and in less
than 100 100 milliseconds the screen
change that's really key for the of the
project the third challenge is up
deployment and always on screens are
really difficult to manage uh I mean we
we made that tradeoff not to have like
industrial screens which are much more
expensive so so well we are in the
consumer world and it's much more
difficult to control completely what
happened on stream so we use MDM
software to deploy remotely so mobile
device management software to uh control
the
tablets but MDM software by itself adds
a layer of complexity usually difficult
to manage or difficult to understand
because they are packed with a lot of
features uh so I mean deploying a new
version is not that easy even now that's
really an area of improvement for us
still uh this we hadn't forcing at
all uh it's quite difficult to have like
htps Connection in a Clos
network uh and on consumer tablets and
but is mandatory for example we thought
we could like do without htps that would
be nice but the MDM software prevented
us didn't want us to connect to deploy
web apps which are not served over htps
so we are in the clo networks where
there are no threat issue at all but we
had to deploy htps but then when you're
in that closed Network how do you
validate certificate and stuff a little
bit of engineering there and lots of few
days I can say uh to solve that that we
hav't Clen really how how long does it
take you to uh like the HPS uh quite few
days I guess three to four days to like
find a walk around first we we wanted to
find a walk around uh trying to use the
MDM software without using hgps but that
didn't work so finally we had have to
find a way to validate
certificate I mean essal
certificate uh that would be used in the
warehouse but not on the public IP
address quite quite
complex uh so now what's next we
launched today so that's a good a huge
my for us thank you uh and what's next
um we have to leverage the data that
that production line produce and that
actually there a lot of opportunity
there so we we every sensor event is
recorded so we know by the milliseconds
how much time it takes uh for I don't
know uh handling the watermelon or
handing a cauliflower and that would
help us a lot to to U uh calculate the
margin that we have in specific order
and to have the purchasing team in their
choices of fruits of vegetables because
we know the associated cost while
preparing the order um and also we have
a lot of uh Improvement still in the
space of reliability so we should be
able to replace sensor tabl light in
less than five minutes without the
intervention of someone from my team are
not there yet at all so yeah lot lot of
work to do there like uh
producing writing sorry processes having
spare parts preconfig kind of stuff
we're not there yet um deploy singly a
new version of the app as I said it's
quite complex uh to have to deploy that
version and you have to understand that
these screens are always on the app has
to replace itself you shouldn't like
relaunch it it has to be like completely
seamless once again it's that done and
and we have to to add a lot of
monitoring uh on the systems everywhere
to be able to prevent and detect
failures before they happen uh but
that's next
step and I guess that's all I had to say
for today I got I got the last video
that's another Warehouse in Madrid uh
that we deployed also and it's a
different system doesn't use the big
plastic boxes but it's a system with one
other at a time in a in a out
books and that's it for the presentation
if you have any
questions what was the development time
in total like when did you start and so
we started designing theem exactly year
ago okay because we thought that we so
we wanted to launch that offer the full
customization
during Q4 this year uh so we had to
prepare that project before because
without the light there's no way we can
like launch that full customization
project but we started designing it a
year ago I guess we found the
sensors in q1 N of q1 and then was
like mainly development from q1 to the
end of Q3
Withers
prority how much is how expensive is One
sensor so One sensor it's it's around
600
okay but then the wiring also with
proprietary you there's a lot of
electrical work I mean when you enter
that all of
industrial uh surface like I mean all
the s are um you need to have a to
provide 24 volt current so it's like
super
specific uh I mean Super common in
automation world and in the automatic
world for ACT world but not really our
space like web
developers and for the biggest well you
said there are 303 people working in the
production line so we have 13 people on
the production line and in the in that
largest Warehouse we have two prediction
light the two prediction light are
equipped so that's 26 employees that may
work at the same time okay so so that's
that makes like a tool of 70 different
products so that 70 different vegetables
and no because you have same produ on
the two production NES One prodction n
should be able to to to have a complete
order but you've got four products per
employee you can go up to 42% vegetables
okay
yeah with the Box they follow the box to
the end or no no no no no they move the
Box yeah yeah yeah that's I mean one
employee is in charge of like four
different FR vegetables and if it's uh
for example a vegetable which is with a
very high demand I don't know potato for
example that's he had only potato in
front of him or her uh and we do only
potatoes because the other issue that we
didn't see there how do you feel the
production L on vegetables that's under
the roof the other side of the prodction
line you've got people uh you know
scanning boxes for traceability and
putting back like new fruits and
vegetables uh on top of the production
line so the production managers for
example um instructing employees said
okay you you are um responsible for
refilling and and Stu exactly exactly
youing and they refal as fast as they
can that's the instruction basically the
prediction has to preder has to be full
all the
time and the W's basically fridge I saw
everyone was check it yeah yeah that was
one of the challenge when we work on
that project because for one our jacket
a few times a long days very cold yeah
it's five degrees I guess or six degrees
okay for the conservation of
the one of the CH you have is to update
the app is it because the screen is 247
always on or or yeah yeah it's 247 okay
but we don't work uh yet uh during we
have only one shift okay um but right
now we so the the tablets are always on
and we'll find a way to like switch them
off automatically during the night it's
not not done yet unless yeah exactly you
don't want that and instead using a web
in wait we well we use a web app so it
can it can refresh uh itself
uh so that's one way of addressing it
but sometimes uh you need to uh so the
the thing is so we we uh the app is
served by the local engine also and we
deplay both at the same time and uh but
yeah one of the ways to do so exactly to
refresh we without the
MDM it's a PM and we mm for
that
okay
one oh that's because um that's the way
we uh ship them uh so around Paris we
have our own trucks and these box fit
perfectly into the truck and the truck
is filled up to the roof and that's a
way to maximize the load in the track
and the the way the order the ERS are
ordered on the prodution line is the I
mean first we're going to put the orders
that have to be in the back of the truck
so we compute the trips uh before before
the day uh for example we have know
2,000 orders to deliver and they're all
in a specific order to be loaded at the
back of the truck if they are at the end
of the
trip a special application
there oh yeah yeah we use like third by
Soft for that it's like super complex
softwares because it has also to take
into account like traffic jams and I
know road which block on pares and
stuff how many orders um will you be
able to to fulfill per day or per
whatever that's a very good question we
don't know yet okay yeah really we don't
know yet uh so we are uh able to uh to
do more than 2,000 orders
uh on one day on one prediction line so
already
already have more than that because so
the the right now the customers order
one week and receive the order the week
after so the shortest we've got is you
you prepare you you make your order on
on Sunday and we deliver on on
Tuesday then you can prepare them on the
day oh yeah yeah we
yeah and did did you do any stress tests
uh for for your application because you
said okay we don't know until
when but the system can go like
much yeah yeah has no like Tech limit
that the limit is in the number of
employees you can have on production
line and
specifically the the pace at which you
can refill the production lineation isue
rather than and and and the the room it
takes to have all the people moving with
boxes uh and filling the prod up that's
the the real issue technically it's all
sorted but operationally yeah yeah
yeah question you said you you sell
vegetables and product that are not they
cannot be sold in other in other shops
is it because other shop just don't want
to sell them or you need to have some
special permission Oh no just they don't
want so because they don't look yeah
yeah
exactly exactly and that's between five
to 10% of the prediction of Which F it's
pretty hard
yes oh so there regulations for for
example
like yeah Qs which are too small we
don't have the right to sell them so we
don't have the right
either but miss shapen carrots I mean
there are no
regulations but yeah people are in
Supermarket you just don't buy
them a subscription model customer yeah
you pay every month no no so it's it's
per week but I mean it's a subscription
with no commitment that means every
Thursday you receive the fruits and the
list of fruits and
vegetables uh and you can choose either
to uh keep the basket or skip it no and
you can suspend any time really no
commitment but I mean there is no check
out you entered your like credit card
when you subscribe and then each week
choose if you want to have the baset or
not and you can add CL
uh basket so we have got another
production system for the all the all
the grocery
products and the part from monitoring
what features do you want to launch in
the future so are are is do you have a
backl already what features yeah yeah
and for like the app and backend and
stuff oh yeah so we line there things
you would like to add is for example if
you want to add like gifts or incentives
to specific customers for example
loyalty programs that's really the kind
of thing we could add very easily on the
screen so I don't know it's your it's
order and have a specific gifts for that
uh that's super easy to like display on
the screen add that gift for example B
to bag in the order super easy to with
that system and that we couldn't do
before I mean there a lot of marketing
SCH that we can now develop building
that
tool okay cool cool thank
you
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