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23-Ind-A4 Production Management · December 2018

Question 5 of 8: Li-Ion Battery Production LP Across Three Plants

Nivaar worked solution (AI-drafted; not reviewed by a licensed engineer)

Notes on this paper

National Technical Examinations — December 2018 — 17-Ind-A4 Production Management. Three-hour, closed-book exam; Casio or Sharp approved calculators only. Format: eight questions, each worth 20 marks (sub-part weights 10/10 as tabulated on the front-page marking scheme); candidates do two questions from Section A and three from Section B, and only the first five questions appearing in the answer book are marked. All eight are solved below for completeness. The paper asks for point-form answers wherever possible; the solutions below use full working for clarity.

Reference texts: Nahmias & Olsen, Production and Operations Analysis (7th ed., Waveland/McGraw-Hill) — forecasting, inventory (EOQ/EPQ) and aggregate planning; Sipper & Bulfin, Production: Planning, Control, and Integration — production scheduling, JIT/kanban and shop-floor implementation gaps; Hillier & Lieberman, Introduction to Operations Research (11th ed.) — LP formulation and project scheduling (CPM/PERT); Pinedo, Scheduling: Theory, Algorithms, and Systems (5th ed.) — parallel-machine scheduling and days-off workforce scheduling; Hopp & Spearman, Factory Physics (3rd ed.) — variability, buffering, and production scheduling; Liker, The Toyota Way, and Shingo, A Revolution in Manufacturing: The SMED System — 5S, Five Whys, SMED and lean root-cause analysis.

Question 5: Li-Ion Battery Production LP Across Three Plants (20 marks)

Question text not reproduced: the examination questions are © Engineers and Geoscientists BC. Open the official past paper (linked at the top of this page) to read the question, then follow the worked solution below.

Check — three-plant scenario; Edison floor is INFEASIBLE
This scenario has three plants (Quebec City, Toronto and Vancouver); Vancouver has capacity for 24,200 batteries/mo and 950,000 kg Li/mo. The Edison Motors ratio is 3:2 Heavy:Medium. Against total system capacity, this Edison floor is Li-infeasible.

Given.

GradeUnit profitMax demand (units/mo)Li requirement (kg/battery)
Heavy (H)$\$12$17,000200
Medium (M)$\$10$19,000150
Light (L)$\$7$14,000100
PlantAssembly cap. (batteries/mo)Max Li production (kg/mo)
Quebec City (QC)15,500850,000
Toronto (TOR)17,500700,000
Vancouver (VAN)24,200950,000

Find. (a) An LP formulation allocating the three grades among the three plants to maximize total monthly profit, plus one other important cost factor the formulation omits; (b) the formulation modified so the Edison Motors order (15,000 units/month, Heavy:Medium $=3$:2) is guaranteed met every month.

Approach. Define a decision variable for each (grade, plant) pair; each plant has two independent capacity limits (assembly units, and kg of Li, since Li requirement differs by grade), and each grade has an independent market-demand ceiling summed across all plants. Although the question asks only for the formulation, solving both LPs (unconstrained, and with the Edison floor added) is a cheap and decisive check on whether the new contract can actually be satisfied.

  1. Decision variables and objective (part a). Let $x_{ig}\ge0$ be the number of grade-$i$ batteries produced at plant $g$, for $i\in\{H,M,L\}$, $g\in\{QC,TOR,VAN\}$. Maximize total monthly profit: $$\boxed{\max Z=12\sum_g x_{Hg}+10\sum_g x_{Mg}+7\sum_g x_{Lg}}.$$
  2. Constraints (part a). Each plant's total assembled units cannot exceed its assembly capacity; each plant's total Li consumed (grade-specific requirement $\times$ quantity) cannot exceed its Li capacity; and each grade's total production across all three plants cannot exceed its monthly demand ceiling: $$\sum_i x_{ig}\le \text{cap}_g\ \ \forall g,\qquad \sum_i \ell_i\,x_{ig}\le \text{LiMax}_g\ \ \forall g,\qquad \sum_g x_{ig}\le \text{Dem}_i\ \ \forall i,\qquad x_{ig}\ge0,$$ where $\ell_H=200,\ell_M=150,\ell_L=100$ kg/battery. This gives $3\times3=9$ variables, 3 assembly constraints, 3 Li constraints, and 3 demand constraints. One other important cost factor omitted here: inter-plant/inter-grade changeover or setup cost — the formulation implicitly assumes a plant can freely mix all three grades within a month at no switching penalty, but a real assembly line likely incurs a setup cost or lost capacity each time it changes grade, which would need either a fixed-charge term per (grade, plant) pair used or a minimum-run-length constraint to model realistically; transportation cost of finished batteries from each plant to the customer/distribution network is a second reasonable answer.
  3. Edison Motors floor (part b). A 3:2 Heavy:Medium mix totalling 15,000 units/month splits as $\tfrac35\times15{,}000=9{,}000$ Heavy and $\tfrac25\times15{,}000=6{,}000$ Medium. “Must be met each month” is a hard floor. The Edison order is new business on top of the existing market, so the market ceilings must also rise by the contract volume. If they stayed at 17,000 and 19,000, the Edison units would silently displace existing customers. The Heavy and Medium demand rows therefore become two-sided: $$\boxed{9{,}000\le\sum_g x_{Hg}\le17{,}000+9{,}000=26{,}000,\qquad 6{,}000\le\sum_g x_{Mg}\le19{,}000+6{,}000=25{,}000}$$ replacing the part-(a) Heavy and Medium demand rows (objective, Light demand row, assembly and Li rows unchanged). An equivalent form uses separate Edison variables $e_{Hg},e_{Mg}\ge0$ with $\sum_g e_{Hg}=9{,}000$ and $\sum_g e_{Mg}=6{,}000$, added into each plant's assembly and Li rows.
ItemResult
Variables$x_{ig}$, 3 grades $\times$ 3 plants $=9$
Part (a) constraint count3 assembly + 3 Li + 3 demand $=9$ (+ non-negativity)
Part (b) modified demand rows$9{,}000\le\sum_g x_{Hg}\le26{,}000$, $6{,}000\le\sum_g x_{Mg}\le25{,}000$ (replace the H and M demand rows)
Bonus: part-(a) LP solved, optimal profit$\approx\$171{,}333$/mo (Medium+Light only — see callout)
Bonus: part-(b) LP with Edison floorInfeasible — see callout
Check — both LPs solved as a bonus check
Solving the part-(a) LP (not required by the question, but a useful validation of the formulation) shows Li capacity, not assembly floor space, is the binding resource at every plant: since profit-per-kg-of-Li is $\$12/200=\$0.060$ (Heavy), $\$10/150=\$0.067$ (Medium), $\$7/100=\$0.070$ (Light), the unconstrained optimum produces zero Heavy, all 14,000 units of Light's demand, and 7,333 units of Medium (profit $\approx\$171{,}333$/month) — and at this optimum every plant's Li constraint binds exactly (QC: 850,000 kg used of 850,000 kg cap; TOR: $\approx$700,000 of 700,000; VAN: $\approx$950,000 of 950,000) while every plant's assembly capacity is well under its cap, confirming Li is the sole system-wide bottleneck.

Adding the Edison floor ($H\ge9{,}000$, $M\ge6{,}000$) makes the LP infeasible: those two grades alone would need $9{,}000\times200+6{,}000\times150=2{,}700{,}000$ kg of Li, but the system's total Li capacity across all three plants is only $850{,}000+700{,}000+950{,}000=2{,}500{,}000$ kg — short by 200,000 kg (8%) even before any Light production or assembly-capacity limits are considered. Losing Seattle's plant is the direct cause: this three-plant system simply does not have enough lithium-production capacity to guarantee the contract, regardless of how production is allocated. This is a genuine, data-driven infeasibility (not a modelling error) and would need to be raised with the customer or resolved by adding Li-production capacity before the contract could be signed.