Artificial Intelligence (AI) the Good the Bad and Ugly of Manufacturing Operations Management

1. ARTIFICIAL INTELLIGENCE THE GOOD – THE BAD & THE UGLY OF MANUFACTURING OPERATIONS
MANAGEMENT
L | C | LOGISTICS
Plant Manufacturing and building facilities equipment
Engineering-Book
ENGINEERING FUNDAMENTALS AND HOW IT WORKS
August 2019
Expertise in Process Engineering Optimization Solutions & Industrial Engineering Projects Management
Supply Chain Manufacturing & DC Facilities Logistics Operations Planning Management

2. Manufacturing Operations
Management Content:
1. Background
2. Standard Process
3. Micro / Crisis Process
4. Turn around /Chaos
Process
5. Artificial Intelligence /
sustainable Process

3. Manufacturing Operations
Background
• Every Manufacturing Operation
has the objective to maximize
production yield, rates, with zero
accidents, environment pollution,
machines breakdown, waste; use
GMP/BRC/FDA/ISO standards;
control its sustainable process
• Continuously finding ways to
expand its capacity through new
technologies, replacing process
with innovation, optimizing use
of resources, creating a platform
to sustained growth, lowest cost
and highest operational net
output
• The objectives are very clear

4. Manufacturing Operations
• To achieve those objectives, all
companies rely on their
managers and their inner culture,
which is different from the labor
force, white collar and technical
staff
• Best companies follows the stable
process management, with great
discipline, organization and time
• Turbulent companies have a
mixture of non stable manager’s
characters, motivated by
authoritarian power display,
dominant image, low knowledge,
creating crisis to display actions
• Chaos companies are run as small
dictators, big mafia bosses style

5. Manufacturing Operations
• Unless you run your own
business you will be working for
someone and your professional
life will depend not on your skills
but on the one to one
relationship with your
management, whatever it is
• Unfortunately you only know the
management culture, only when
you already made the move
• Regardless of what management
style you will be in, keep your
participation and contributions at
a professional level, consistent
and actions - results predictable
• When you have the opportunity
to go to a healthier management
just do it, don’t wait, just go

6. Manufacturing Operations
• The future of management is in
the coming Artificial Intelligence
management applications,
replacing the endless meetings
• Most daily routine meetings are
repetitive, informative, waste of
time for all the participants and
decisions are also repetitive; even
the root – cause analysis and
statistics results are repetitive
• If the management is by process
then the decision making is faster
• If the management is by crisis
then only by having a crisis can
have management “actions”
• If the management is by chaos, it
doesn’t matter, someone will die

7. Manufacturing Operations
• Standard Process
• Get to know your production line
machines, design performance pa
rameters specs and tolerances
• Start by simulating a typical
customer order production time
• Know your balanced production
line designed capacity units/time
• Know your balanced planed
production line required capacity
• Know your actual balanced
production line used capacity
• Know your machine(s) cycle time
• Know your labor ergonomics
• Know your labor requirements
• Get to know the machine(s)
setting steps sequence & time
• Get to know your machine(s)
materials preparation, loading
time and generated waste to
start
• Explain the gap between actual &
planned capacity utilization
– Machine(s) breakdown waiting time
– Machine(s) waiting spare parts
– Machine(s) breakdown repair time
– Machine(s) re-setting time
– Machine(s) out of setting specs time
– Machine(s) idle un attended waiting
– Machine(s) setting fine tuning time

8. Manufacturing Operations
• Balancing a production line is the
first step, and it only takes a few
parameters and calculations to it
• Start by the lowest speed
machine in the line, and then get
all other machines calibrated to
synchronize to the same speed
• If you use manpower, work your
ergonomics parameters values
and find the balanced use of man
power required to keep the line
balanced
• Line balance eliminates waste
• Check all machines – equipment
do not have any obstruction to a
smooth material/FG flow through
• Production line speed is related
to the making product dimension
as machines speed are adjustable
and machine calibration setting
keep the line balanced
• If your production line is labor
intensive, you have to balance
the lines at different speeds
based on the involved manpower
skills, working in a pool or team
• Line balancing requires the use of
a simulation program to fine tune
the line before it starts running
• A computer simulation takes just
a few seconds to give you the
best option as per your resources

12. Manufacturing Operations
• Management by process leads to
Artificial Intelligence Applications
• This means across the production
process, data is collected in real
time, to a support AI computer
system, then, all data is analyzed,
triggering decision, information
ands sustaining the process as it
should be, minimizing deviations
• AI applications, are integrated to
a full manufacturing accounting
ERP computer system, so the
data is captured only once, along
the manufacturing process
• It all start with the ERP customer
order, which is then planned by
the AI application, generating all
• working instructions, for the
production line(s) operators,
warehouse, delivery transport,
inventories control, procurement
orders directed to authorized
suppliers, maintenance, quality
• Along the process, as the work
instructions execution progress,
data is collected in real time
through process flow sensors,
and analyzed by AI application
• Dash Board visual graphs are
prepared by the AI application,
including all statistics reports,
occurred problems root cause,
adequate corrective decision –
action, and directed work
instructions to concerned site

13. Manufacturing Operations
• Continuous data collection from
production line machine(s)
– Bill of Materials input (ratio to FG) in
each step of the production line
– Good Quality Finished Goods output
• Production waste
– Machine(s) starting waste
– On-going production operator waste
– Machine(s) defect waste
– Raw materials production waste
• Production on-hold by quality
– Did not meet customer specs
– Did not meet technical specs
– Not clear what is the problem

14. Manufacturing Operations
• Computer calculated parameters
– Actual Production yield
– Actual Production rates
– Overall Equipment Utilization
– Breakdown MTBF, MTTR
– Customer order fulfillment % & qty
• Check list of activities to record
– Preventive Maintenance start/stop
– Corrective maintenance start/stop
– Breakdown repair start/stop
– Production operation start/stop
– Utilities readiness start/stop
– Health & safety start/stop
– Cleaning machine(s) area start/stop
– Waste clear & removal start/stop

15. Manufacturing Operations
• An organized production process
without the use of Artificial Intelli
gence Application, the time for d
aily routine meetings is < 50’
• It is not informative, it focus on
one objective, making a decision
on an issue not covered by the ex
isting process flow
• There will be a brain storm
workshop session to improve the
existing process; only selected pe
ople will be part of the team
• Once the process is updated it
will be used as the new standard
• Routine meetings are kept to the
minimal time usage, with respect
and professional participation

16. Manufacturing Operations
• Micro /Crisis Process
• is the favorite mode of managers
who work full time from their des
k and meeting rooms
• They need to create a crisis to be
visual, authoritarian, with never e
nding harassment, complains an
d show of power
• Highly political and influential at
the top management
• kind of good communicators, but
ignorant about what is really hap
pening at the production floor sin
ce they seldom go to the floor
• If they go, it is just to find a crisis,
and use it, for their expertise in vi
sual crisis management
• They are very obedient to all
corporate head office request,
and very charming with
corporate visitors, always
preparing a good visual show to
impress the visitor
• Their corporate diplomacy is the
opposite continuous harassment
behavior, towards all technical
and office staff, and they are
good actors, and public speakers
• However they cover all big issues
like low production yield, rates,
process quality, waste generators
• Love to shuffle the technical and
administration staff like cards
• Practice Kaizen, Lean, Six Sigma,
Continuous Improvements,

17. Manufacturing Operations
• Turn around /Chaos Process
• To understand this management
style, you have to understand
how the Mafia operates
• The threat is just like “ kill or be
killed”, or management by results
• Management by Walking around,
only to find anything to shoot out
someone, create terror, panic
and get nervous; not to be the
next one to be ‘killed’ literally
speaking
• Some companies hire technical
and management staff, only for
the probation period, and they
never pass it, meanwhile they are
fully exploited, blue collar slavery
• Turn around Managers’ speech
• “No leadership to decide what to
do, that is totally wrong, leaders
most see everything and clear, cl
ean and make all ready, never be
the messenger, do and see by yo
urself, before you comment and
open your mouth, be truthful and
test and check functionality, and
verify if it works, before you say it
doesn’t work, or it is garbage; mo
st have passion for your work, no
t just have the job”
• “You need to know where you
are and where are you going, busi
ness is all about people”

18. Manufacturing Operations
• “go only by results not by
incentives, nothing matters, only
the results not about the relation
ship, just like any machine works
by efficiency”
• “help to make sure the system
works, target must be measured i
n money, most accelerate the lea
rning curve to improve and self le
arn to think”
• “Go after the magnitude not the
quantity, without doing your resp
onsibility you get nothing, so do y
our thing”
• “Be reckless then get out by
yourself”, etc……………………..

19. Manufacturing Operations
• In other industrial societies, their
paradigm is found in the roots of
their education and cultural base
• Breaking the rules on purpose till
get caught is the standard
• The ability to think logically and
rationally is another fall down
• Wasting the working time in non
working issues is also cultural
• Rather than been multi tasking
and self efficient, there is the
tendency to work in group, which
is not necessarily, team work
• High absenteeism, and
dependency on one man memory
or operational - technical skills
• Artificial Intelligence / sustainable
Process
• In advanced industrial societies
like Switzerland, Germany,
Japan and other European
countries; management is far
from ruthless, however very high
in their self discipline, order, and
systematic approach towards
every aspect of their working life,
besides their daily public and
social life
• People are very efficient in their
own profession, what ever it is,
and that is the result of their own
education system, from kinder
garden to vocational or university

20. Manufacturing Operations
• Artificial Intelligence Applications
are going to remove many of the
inefficient managers, operators
and technical staff, as their direct
contribution is to be eliminated
• The side effect of this, is a change
on management practices, and a
sustainable continuous reliable
production decision making
process flow with less managers
• AI is to force managers to be
more professional, technical and
process flow, and ERP-IT oriented
• AI, has its roots in computer
systems, programming languages,
control engineering, robotics,
automation, mechatronics
• The next ERP computer systems,
have to be integrated to Artificial
Intelligence Application, in both
Manufacturing, and Retail Supply
Chain Operations Management

22. Manufacturing Operations

23. Thank You
L | C | LOGISTICS
Plant Manufacturing and building facilities equipment
Engineering-Book
ENGINEERING FUNDAMENTALS AND HOW IT WORKS
ARTIFICIAL INTELLIGENCE THE GOOD – THE BAD & THE UGLY OF MANUFACTURING OPERATIONS
MANAGEMENT