Almost all companies work with constantly grown SKU’s and raw materials numbers, that leads to working with smaller and smaller batches, shorter and shorter lead times and higher and higher quality standards which brings high complexity in effective production flow management. To manage and visualize Information Flow became necessary condition for effective production, business management or any kind of improvements – LEAN, TOC, Six Sigma or TLS.

1. CSI approach to your Production
Management
Director Andrius Gudaitis 2013.05.171

2. Nova days key success factor in production and
business environment is a correct Information
Flow Management.
Almost all companies work with constantly grown SKU’s and raw materials
numbers, that leads to working with smaller and smaller batches, shorter
and shorter lead times and higher and higher quality standards which brings
high complexity in effective production flow management.
To manage and visualize Information Flow became necessary condition for
effective production, business management or any kind of improvements –
LEAN, TOC, Six Sigma or TLS.
2

3. Meaning of Proginta’s service is to arrange company Information Flow in
such way that Company Management or Lean, TOC, Six Sigma consultants
could easily recognize where to put their attention to increase efficiency of
production flow and reliability of client service.Low with peaks
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week
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4. Proginta inc.
— Proginta inc. combine different competences, software
development and ERP deployment with deep international
consultant expertise based on supply chain and production
management using latest TOC and LEAN tools and
methodology.
— Proginta inc. provide Information Flow management services
in Ukraine and Europe from 2008. Services included classic
consulting, IT solutions, daily work with data flow and Reports.
The goal of our service is to help a client to improve their
financial result.
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5. We would like to repeat
Proginta inc. strive to present analytical information in a way that
it is easily comprehended even without consultant’s help. Thus,
company management gets a clear understanding where to
focus their efforts for a much greater improvement in current
results.
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6. Methods we have competencies in:
6

7. Proginta are focusing on three main flows or
processes
Information flow
Money flow
Products and services flow
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8. Proginta offer a long term service of:
—Systemic analysis of the entire company
or
—Localized analysis of client’s choice according to
Lean and/or TOC as a pilot project.
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9. Systemic analysis
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10. Quantum cryptography
vs. Business
10

11. Production efficiency depends on the efficiency of every link in
production chain: supply, production departments and logistics.
Problems that disrupt production plan are generally known and taken
care off as they arise.
This ―fire-fighting‖ method does not provide systemic improvement,
because it fights symptoms and not the cause of the problems.
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12. Systemic analysis must
specify production
disturbance causes and
their ratings.
This allows to determine
causes that affect
production plan the most
weekly and monthly.
0
5
10
15
20
25
30
35
Defective RM
Order sequence changes
Issues with working tools
Quality defects
Equipment failure
Raw materials/components
supply
Raw
materials/co
mponents
supply
25%
Equipment
failure
12%Quality
defects
16%
Issues with
working
tools
21%
Order
sequence
changes
7%
Defective
RM
19%
12

13. Production process
Orderdispatch
Materialarrival
Materialordering
Materialissuing
ElementtransfertodepartmentX
ElementtransfertodepartmentY
Productarrivaltowarehouse
13

14. Systemic analysis measures:
— Reliability of material supply;
— Planned production starts;
— Timely transfers between departments;
— Timely production task completions;
— Timely order dispatches;
— Etc.
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15. Production process
Orderdispatch
Materialarrival
Materialordering
Materialissuing
ElementtransfertodepartmentX
ElementtransfertodepartmentY
Productarrivaltowarehouse
Measures in selected points:
— DDP%,
— OS,
— TVD.
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16. Rating’s purpose:
DDP (Due Date Performance) % indicates reliability of a
link.
If a link does not have buffer or excess production
capacity, then the following link receives a lag.
Common causes:
— Untimely material supply;
— No material supply;
— Previous link changed production tasks;
— Incorrectly planned production scope;
— Etc.
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17. Rating’s purpose:
OS – Over Stock
Common causes:
— Overprotection;
— Production oriented efficiency;
— Preceding departments starts tasks too early;
— Incorrectly planned queue in preceding departments;
— Large production batches policy;
— Etc.
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18. Rating’s purpose:
TVD (throughput value days)
This rating evaluates financial lag of delays.
It allows to analysis financial impact of delays and to
allocate TVD points to the source of delay.
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19. Required data:
DDP%
Initial data – detailed production plan:
— Production start time, end time and planned
amount;
— Equipment preparation time;
— Single element processing cycle;
— Equipment standby time.
Operations data:
— Reasons for changing production plan;
— Amount produced between X and Y hours;
— Accumulated lag.
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20. Data required for planning:
— Number of resources in a department;
— Resources’ work schedule;
— Shifts’ work schedule.
20

21. Data required for planning:
— Material supply schedule
Evaluation of material supply
reliability (ordered vs. arrived)
Material arrival
terms (lead time, on
request)
Procurement plan
forming
21
,etc.
Your ERP system

22. Data (or VSM) required for planning:
— Production route.
— System that plans
according to production
routes.
22

23. Data entry forms - Production routing (operations sequence and resources)
description
If current systems
cannot store required
data…
23

24. Data entry forms – Bills of material and Product assembly tree
If current systems
cannot store required
data…
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25. Data entry forms – Job sequence management with raw control
If current systems
cannot store required
data…
25

26. Data entry forms – Job execution management with barcode or custom
instruments
If current systems
cannot store required
data…
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27. Data entry forms – Job sequence management per resource usage
If current systems
cannot store required
data…
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28. Acquiring actual data
Supply Production Warehouse
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29. Acquiring actual data
Procurement data:
1) Ordered materials: item number, quantity, planned delivery time;
2) Materials’ total received quantity;
3) Factors that cause delivery lag;
4) Reasons for changing delivery time before delivery term.
First two acquired from business management system, others – from
analysis.
Supply Production Warehouse
29

30. Acquiring actual data
Production data:
1) Does the task have all required materials?
2) Which tasks executed according to plan?
3) What are the reasons for changing production plan?
4) What have caused production lag?
5) How tasks are queued?
6) What production facilities are required?
Evaluate how much data is in BMS (SAP, Oracle & etc) and how
much to give to external system.
Supply Production Warehouse
30

31. Acquiring actual data
To collect information that is transmitted
between work centers/departments required :
1) What was the plan?
2) What was produced at a specified time and in
what quantities?
3) What have caused lags?
4) How much spoilage was produced? What was
it?
5) What was material spoilage?
Is it possible to indicate in IT system, that
department has excess resources or buffer?
Supply Production Warehouse
31

32. INSTRUMENTS:
+
Acquiring actual data
Supply Production Warehouse
32
Bottleneck operations data:
1) How production is queued?
2) What is equipment's preparation time?
3) What is the time for single element cycle?
4) What causes lags?
5) How much spoilage produced? What was it?
6) What was material spoilage?
7) Etc.
Data sources include automated data
collection systems (Lean2S) and IP video
cameras monitoring operations or employees’
behavior.

33. Acquiring actual data
Orders data:
1) What is order dispatch plan?
2) How many orders dispatched according to plan?
3) What have caused lags?
4) Reasons for changing dispatch time before dispatch term.
First two acquired from business management system, others –
from analysis.
Supply Production Warehouse
33

34. Our aim to identify what causes plan changes and lags, order
completion lags, production starts too early or produce to
much.
It enables to isolate recurring causes that adversely affect the
results.
It also enables systematic application of Kaizen or POOGI
improvement mechanism.
34

35. Automated data
collection
35

36. Simple & Smart
solution
36

37. The importance of data transmission reliability
While researching production efficiency solutions we discovered that data
reliability is very important:
Given example demonstrates data distortion. First chart depicts actual work cycle. Second charts
depicts situation when there were no connection to database between minutes 5 and 10:
— System did not record 7:00–9:00 downtime.
— This distributed and hid the 5:00–6:00 spike.
— Spike that occurred right before the downtime compensated the latter. This would not be
visible in summarized data and would not draw attention to such event.
Summarizing
distorts data.
People who make decisions
divide into camps: those
who agree with the data and
those who do not.
People who do
not agree with
the data do not
participate in
decision
realization.
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2
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pcs/min (from 05 to 10 min lost connection)
pcs/min lost connection

38. Protection against data loss
Considering possible data loss, we have implemented
solutions that minimize the risks to an absolute minimum:
1) Data receiver preserves data of up to 10 hours of work
while database is down.
2) Data receiver preserves collected data indefinitely while
database is down.
3) Software informs personnel via e-mail or SMS when
communication is down, allowing quick troubleshooting and
data preservation.
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39. Data integrity
Companies usually use various types of equipment from
different vendors.
Consequences of processing data by different software:
1) Different software presents the results differently.
2) Users must learn what those results mean and what to
look at.
3) There is no way to analyze equipment interdependences.
4) Employees who move to another department may have to
learn new analytical tools that may considerably differ from
the previous ones.
39

40. Flexibility of our equipment
Because we are the developers, we are able to adapt our
solution to a specific project.
Data collection unit is constructed using industrial controller
(PLC) that enables to:
— Read data from any type of sensor.
— Adapt data collection algorithms to specific cases.
— Control external equipment.
— Accumulate data internally when communications are down.
Data transferred to PC using:
— Direct connection via COM port.
— Industrial grade wireless connection.
Data collection from external systems:
— We implemented means to exchange data with external
systems.
— As the software developer, we are able to adapt data
exchange between any hardware and software.
— It is possible to export collected data to Your ERP system.
Duomenų mainai
su išorinėm
sistemom
40

41. Objectives
— Generating analytical reports. The purpose of the
analytical reports is to identify negative factors using
historical data.
— Identifying negative factors in real-time. The purpose of
real-time analysis to inform personnel about identified
negative factors ASAP.
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42. Analytical reports
Measurements and Δ change:
EA – Equipment Availability
EEP – Equipment Efficiency Performance
EQP – Equipment Quality Performance
OEE – Overall Equipment Efficiency
Machine operation and tuning
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-60%
-40%
-20%
0%
20%
40%
60%
80%
100%
120%
EA
EA ∆

43. Spoilage analysis
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44. Visualizing equipment operation
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45. Real-time analysis:
— Report workflow status every two hours.
— Notification about unplanned downtime that is not not
resolved in predefined time.
— Notification about lag exceeding predefined time interval.
(For example through text message)
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46. Our proposal -
to start from an
analysis stage:
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47. Analysis achievements:
How and when does information flow now?
Identify what causes information lags.
Assess what current information we can use.
Identify current system’s resources that we can use for analytics.
Determine external IT tools required for systemic analysis.
Develop a project to fill information gaps in the current system.
Define responsibilities for entering information.
Develop a project scope and estimate budget for systemic analysis data collection and processing.
47

48. Andrius Gudaitis
Phone +370 37 30 08 12
Mobile +370 699 9 26 59
E-mail andriusg@proginta.lt
Website www.lean2s.eu
www.facebook.com/proginta
Darius Radkevičius
Partner
Mobile +370 698 4 10 27
E-mail darius.radkevicius@gig-europe.eu
48

49. Proginta was created to be your business personal CSI
(Corporate System Investigator)!
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