Makespan -
Production
Planning & Scheduling Solutions Ltd.
“EFA” a Production Scheduling Algorithm and Manufacturing Software
EFA, Evenly Feeding Algorithm is an Advanced Planning and Scheduling Software (APS) which allows manufacturers to effectively manage an important phase of the Supply Chain. EFA is designed for factories producing a variety of products, mainly Job shops, Flow shops and assembly lines. It is based on a unique algorithm designed to optimize production, reduce the total lead-time (makespan) and maximize throughput and profit. This is done by efficient utilization of the plant’s resources.
The Advantages of APS Systems
APS –
Advanced Planning and Scheduling Systems, have two main advantages. The first,
is their ability to generate feasible plans. Together with an effective
Production Control System and reliable data, the APS system enables
the manufacturer to commit and respect, agreed delivery dates. It also enables
the planner to improve control on raw materials and work in process inventory
(WIP). This feature is common to most APS systems. 
The
second, is their ability to utilize the plant’s resources efficiently and to
optimize production. This feature is what makes the difference between
one APS system and another one.
The
difficulties of optimizing production are described below.
The
Scheduling Challenge
Optimizing production involving sequencing jobs is
highly problematic. The problem is known as "NP HARD", meaning - "Non Polynomial
Hard" problem, or in other words a problem which has no mathematical
solution. The number of sequences that could be created out of M jobs, M=M1+M2
(see the shop floor schematic diagram) is the
factorial of M or M! (For example the number of sequences that could be created
out of 20 different jobs is approx. 2*1018 and out of 25 jobs is
approx. 1.5*1025). Each
sequence could result in another total lead time. The sequencing effect on the
total lead time can be seen in a simple example..
The difference between the shortest total lead time and the longest, could be
very high. In our Casting Plant example the total lead time of three sequences
are 152, 195 and 218 hours respectively.
The only theoretical way to find the optimal sequence is to calculate the total
lead time in every sequence and select the shortest one, but the huge number of
sequences (for let us say M greater than 15 jobs) is beyond the scope of
capability of computers
or even super computers to calculate in a reasonable time.
However
for practical purposes, a near optimal solution can be generated by an effective
heuristic algorithm.
Finding the optimal sequence is the first and major step to optimize production, the next step is to decide and allocate the process machines for each job in every work center.
The Correlation
of the Plant’s Profit to Optimal
Schedule
Shortening lead times decreases manufacturing and WIP
expenses, in addition it enables the planner
to
increase the throughput, and accept more customer orders in a given period.
Sophisticated scheduling as
compared to poor scheduling could increase the throughput by 30% - 40%
and as compared to reasonable scheduling
by 15%-20%.
The extra throughput, with almost no additional
cost (except raw materials); and the reduction of work in process inventory
(WIP) will
considerably
affect the plant’s profit.
|
# |
Sales |
Raw
Materials (k$) |
Other
|
Profit |
Increase of Profit (%) |
|
1 |
1000 |
400 |
400 |
200 |
|
|
2 |
1150 |
460 |
400 |
290 |
45 |
In order to see the correlation between optimal schedule and plant’s
profit let's assume an increasing throughput of 15% in a factory with the
following monthly profit/loss data: Sales= one million dollars, Raw materials expenses=
$400,000, other expenses= $400,000, Profit= $200,000. The table at the right
shows that the increase of profit is 45%.
The increasing profit is unique to each
factory
and
depends mainly on the raw materials part of the sales.
Although the correlation between optimal schedule and plant’s
profit
varies from one plant to another.
the benefit/cost of software based on sophisticated algorithm that could eliminate waste,
reduce the total lead time and increase profit could be much higher than any other
improvement process.
Some managers
are not aware of it. This is because the logic behind it is not straightforward
and the influence of optimal sequence, on the total lead time and profit is not
self-explanatory.
About EFA Software
The EFA
software is based on the EFA algorithm; its advantage on the Bottleneck approach
(TOC)
and JIT is described in a separate article, please link to "EFA Algorithm". In addition our system
enables the planner to run two other planning procedures:
-
EDD, Earliest Due Date. (Actually
this well known procedure was written in order to have a reference enabling the evaluation
of the performance of EFA.)
-
SLP, Self Planning Procedure, scheduling
via an interactive mode, using a “what if” approach, beginning with schedules
either obtained from EFA or EDD or generated through SLP.
Implementing our system doesn't
require any special arrangements or changes on the shop floor. Operating it is
very simple, especially the EFA and EDD procedures, both run automatically;
in addition the planner can intervene almost at every stage of the scheduling
process.
It is recommended the EFA be operated together with systems you might
already have like ERP, MRP etc. EFA will obtain the relevant input data from your
system data base and operate as the planning brain. If such a system does not
exist, the relevant data could be created manually using spreadsheet (EXCEL) or
any text editor.
EFA runs on a PC under
any
version of
Windows.
For more details on our scheduling algorithm and software please link to
"Sequencing Effect", "why EFA" and "EFA Algorithm".
To obtain an impression on the implementation of our software please link to the examples of planning production in a "Casting Plant" and "PCB Plant".
