23-Ind-A4 Production Management · December 2018
Nivaar worked solution (AI-drafted; not reviewed by a licensed engineer)
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 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.
SMED (Single-Minute Exchange of Die) is a lean methodology, developed by Shigeo Shingo at Toyota, for reducing equipment changeover time — the time between the last good part of one production run and the first good part of the next — down to “single-digit minutes” (under ten). It works by separating every changeover task into two categories and then systematically shrinking both: (1) internal setup elements, which can only be done while the machine is stopped (removing the current die, bolting in the new one), are first correctly sorted apart from (2) external elements, which can be done while the machine is still running the previous job (fetching the next die and its tools, pre-checking bolt torque specs, staging fixtures on a cart beside the machine); internal steps are then converted to external wherever possible (pre-heating a die, pre-assembling a sub-fixture off-line); and finally both remaining internal and external elements are streamlined (quarter-turn clamps instead of bolts, guide pins for automatic alignment, standardized die heights that need no shimming).
Example. A stamping press changing dies between two part numbers originally takes 90 minutes: the operator waits for the crane to bring the next die (internal, but purely a waiting/logistics problem), unbolts eight mounting bolts of varying sizes, manually shims the new die to the correct height, and re-torques all eight bolts. Applying SMED: the next die is pre-staged on a cart beside the press and inspected while the current die is still running (external); the eight assorted bolts are replaced with quarter-turn clamps on a standardized die-base height (streamlining); and a locating pin fixes horizontal alignment automatically (eliminating the manual shim step). The changeover, now only “crane the pre-staged die in, engage four clamps, verify with a go/no-go gauge,” falls from 90 minutes to under 8 — enabling smaller batches (since setup no longer dominates the cost trade-off), which is precisely the enabler JIT/kanban production depends on.
Kanban is a pull-based visual signal system: a downstream station only produces (or a supplier only ships) when an empty kanban card or bin arrives, and the number of cards in circulation for a part sets a hard ceiling on the WIP for that part. Sizing that card count correctly requires the demand for the part to be reasonably stable and repetitive, so a fixed number of cards, once tuned, keeps the line fed without either starving or over-producing.
Example situation: a high-volume automotive fastener/sub-assembly line — e.g., an assembly plant that consumes the same bolt, bracket, or wiring-harness sub-assembly on every unit of a single vehicle model, shift after shift, at a steady, well-forecast daily rate. Kanban works well here because: (1) the part number is genuinely recurring, so a card (or bin) attached to that specific part has a stable, calculable replenishment cycle rather than a one-off routing to design; (2) demand is smooth and predictable enough (a fixed number of vehicles built per shift, each needing exactly one of the part) that the standard card-count formula $N=\dfrac{d(L+S)(1+\alpha)}{C}$ converges to a sensible, non-fluctuating number of cards; (3) the supplying process (an internal feeder cell or an external supplier) is close enough and reliable enough in lead time $L$ that a small number of cards can keep the line fed without excessive safety stock; and (4) the simplicity of a visual pull signal — no computer schedule, no expediting — removes planning overhead precisely because there is nothing complex to plan: the same part, in the same quantity, arrives on the same cadence indefinitely. This is the mirror image of the job-shop case where kanban fails: instead of a different part and routing every job, kanban here regulates one part with a steady, repetitive pull, which is exactly the condition the technique is designed for.
