Chemical Engineering July 2023 - 36

as it may be implemented using a
spreadsheet program, such as MicroSoft
Excel. Note that the ATM with
maximum inventory limit is also useful
for material that may encounter
quality degradation due to prolonged
storage (see Ref. 6, for example). n
Edited by Gerald Ondrey
Acknowledgement
The authors would like to acknowledge Wooi Keat Tee
and Lakshmi Vaideeswaran for their input in this work.
References
1. Axsom, T., 10 Trends Shaping the Future of Supply Chain
Management, www.fictiv.com, 2022, accessed Oct. 2022.
FIGURE 4. Seal inventories in all facilities are displayed in this grand composite curve
Scenario 1: Without maximum
inventory constraint. In this scenario,
no constraint was set for the
maximum inventory units across all
facilities. The ATM is solved using
MS Excel, the setting and results of
Solver are shown in Figure 2. Since
the inventories of three plants are to
be considered, the ATM is modified
such that total demand in Cells C5-
C16 in Figure 2 is the total demand
of all plants, that is, the sum of Cells
G5-G16 (Plant A), C21-C32 (Plant
B) and G21-G32 (Plant C). Similarly,
Cells D5-D16 (central warehouse)
is given as the sum of cells H5-H16
(Plant A), D21-D32 (Plant B) and
H21-H32 (Plant C). Besides, these
Cells are set as " changing variables "
so that they may be varied to meet
the demands in individual plants. The
objective function is to minimize the
total cost (Cell M3). As discussed earlier,
constraints are needed to ensure
supplies and inventories in Columns
D, E, H and I are set to non-negative.
Entries with a zero for inventory cells
indicate the pinch month of the plant,
where the inventory reaches its minimum
- that is, one unit (for example,
September-December for Plant C).
Figure 2 also shows that solving
the ATM resulted a total cost of
$87,500 with 35 pump seals to be
purchased in January. These seals
will build up the company inventory
(see Column E) to cater for demand
throughout the year. In other words,
all seals are to be purchased in January,
so that they may be used in the
plants throughout the year.
Scenario 2: With maximum inventory
constraint. In the previous sce36
nario,
when no constraint is set, the
company purchases all necessary
pump seals at once in January, in
order to meet all demand throughout
the year. Although it may be advantageous
to buy the units in bulk to
enjoy lower purchase and shipping
fees, this entails a large financial cash
flow for the month of January, as well
as requiring a large inventory space.
In this scenario, a maximum of eight
units is set as a new constraint for
every month, given as in Equation 5
(other constraints remain identical).
It < 8, for all t
(5)
As shown in Figure 3, this new constraint
is imposed for the actual inventory
(Column E). The results of
ATM indicates
that a degenerate
solution is obtained, with minimum
purchase price of $87,500 that is
identical to that in Scenario 1.
Due to the maximum inventory
constraint, the model determines that
a different number of pump seals will
be purchased throughout the year.
Doing so leads to a lower inventory of
pump seals, and avoids a large cash
flow in January, as well as the need
for a huge storage space.
To better visualize the inventory
levels of all facilities, the grand composite
curves are plotted and shown
in Figure 4.
Concluding remarks
A recently developed optimization
technique called the automated targeting
model (ATM) was demonstrated
for its application in inventory
management. It is particularly useful
2. Singhvi, A., Shenoy, U. V., Aggregate planning in supply
chains by pinch analysis,. Chem. Eng. Res. Des. 80, pp.
597-605, 2002.
3. Singhvi, A., Madhavan, K.P., Shenoy, U. V., Pinch analysis
for aggregate production planning in supply chains, Comput.
Chem. Eng., 28, pp. 993-999, 2004.
4. Foo, D.C.Y., Ooi, M.B.L., Tan, R.R., Tan, J.S., 2008. A
heuristic-based algebraic targeting technique for aggregate
planning in supply chains, Comput. Chem. Eng., 32,
pp. 2217-2232, 2008.
5. Foo, D.C.Y., 2016. Automated targeting model for aggregate
planning in production and energy supply
chains, Clean Technol. Environ. Policy 18, https://doi.
org/10.1007/s10098-015-1082-y.
6. Andiappan, V., Foo, D.C.Y., Tan, R.R., Automated targeting
for green supply chain planning considering inventory
storage losses, production and set-up time, J. Ind. Prod.
Eng., 39, pp. 341-352, 2022, https://doi.org/10.1080
/21681015.2021.1991015.
7. Chua, X.Y. and Foo, D.C.Y., Optimization of cogeneration
system and fuel inventory with automated targeting model,
Clean Technol. Environ. Policy, 23, pp. 2,369-2,383,
2021, https://doi.org/10.1007/s10098-021-02150-8.
Authors
Hoong Teng Loh (Phone: +60165647623;
Email: lhtloh20@hotmail.com)
obtained his integrated
master degree in chemical engineering
at University of Nottingham
Malaysia. He currently works
in semiconductor industry as process
integration engineer. His research
work includes the simultaneous
optimization of mass
exchanger network and direct reuse/recycle network.
Dominic C. Y. Foo is a professor of
process design and integration at
the University of Nottingham Malaysia
(Broga Road, 43500 Semenyih,
Selangor, Malaysia; Phone:
+60(3)-8924-8130; Fax:+60(3)8924-8017;
Email: dominic.foo@
nottingham.edu.my). He is a professional
engineer registered with
the Board of Engineers Malaysia, a
chartered engineer registered with the Engineering
Council of the U.K. and a Fellow for the Academy of Science
Malaysia. He developed various process-integration
techniques for resource conservation, CO2 reduction
and production planning. He has won several industry
awards and has published more than 200 papers in a
variety of engineering journals. He obtained his B.Eng.,
M.Eng. and Ph.D., all in chemical engineering, from Universiti
Teknologi Malaysia.
CHEMICAL ENGINEERING WWW.CHEMENGONLINE.COM
JULY 2023
http://www.fictiv.com https://doi.org/10.1007/s10098-015-1082-y https://doi.org/10.1007/s10098-015-1082-y https://www.doi.org/10.1080/21681015.2021.1991015 https://www.tandfonline.com/doi/full/10.1080/21681015.2021.1991015 https://www.doi.org/10.1007/s10098-021-02150-8 http://lhtloh20@hotmail.com http://WWW.CHEMENGONLINE.COM
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