23-Ind-A4 Production Management · May 2013
Nivaar worked solution (AI-drafted; not reviewed by a licensed engineer)
National Technical Examinations — May 2013 — 98-Ind-A4 Production Management. Three-hour, closed-book exam; Casio or Sharp approved calculators only. Format: seven questions, each worth 20 marks (sub-part weights as tabulated on the front page); only the first five questions appearing in the answer book are marked, so candidates effectively choose 5 of 7. All seven 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) and aggregate planning; Sipper & Bulfin, Production: Planning, Control, and Integration — production-management systems; 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, makespan and tardiness; Hopp & Spearman, Factory Physics (3rd ed.) — variability and production-system inefficiency; ISO 9001:2015 and the Toyota Production System literature — quality management (TQM) and 5S/lean.
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.
Little's law states that, in any stable production or service system, the average number of items in the system (work-in-process, $L$) equals the average arrival/throughput rate ($\lambda$) multiplied by the average time an item spends in the system (flow time, $W$): $L=\lambda W$. Its significance is that it holds for essentially any queueing or flow system — a single machine, a whole factory, or a hospital emergency room — regardless of the arrival pattern, service-time distribution, or dispatching rule, as long as the system is in steady state. That generality makes it one of the few "free" quantitative levers a production manager has: if throughput $\lambda$ is fixed by demand, the only way to cut flow time $W$ (and hence lead time, a major driver of customer satisfaction and cost) is to reduce the amount of work-in-process $L$ sitting in the system. This is the theoretical justification behind WIP-capping systems such as kanban and CONWIP — by physically limiting $L$, a plant forces $W$ down without having to touch capacity. Little's law is also a cheap diagnostic: measuring any two of $L$, $\lambda$, $W$ on the shop floor immediately gives the third, exposing hidden inventory or excessive cycle time without a full simulation study.
5S (Sort — Seiri, Set in order — Seiton, Shine — Seiso, Standardize — Seiketsu, Sustain — Shitsuke) is a structured workplace-organization method from the Toyota Production System that removes clutter, gives every tool and part a labelled, visually obvious home, and keeps the standard through periodic audit and habit-building. Its significance is disproportionate to how simple it sounds: a disorganized workstation hides problems (a missing tool, a leaking machine, an out-of-spec part) inside visual noise, and searching for misplaced items is pure non-value-added time (muda). By making abnormalities visually obvious — a shadow board with an empty outline, a marked floor area that is not empty — 5S is usually the first step of any lean or TPM (total productive maintenance) rollout, because it builds workforce discipline and creates the visual baseline that later tools (kanban boards, andon signals, standardized work) depend on. Companies frequently find that safety incidents and minor stoppages drop measurably after a genuine 5S implementation, simply because hazards and defects that used to hide in clutter are now visible immediately.
Interchangeable parts are components manufactured to a tolerance tight enough that any unit of a given part can be substituted for any other unit of the same part in final assembly or field repair, without hand-fitting. Historically (Whitney's musket contracts, then Ford's moving assembly line) this was the single innovation that converted manufacturing from craft production — where a skilled fitter custom-adjusted each mating part — to mass production, because it decoupled parts fabrication from final assembly: parts could be made in batch, in parallel, by less-skilled labour, and assembled by workers who no longer needed fitting skill. Its significance today is that it is the precondition for every modern high-volume manufacturing and repair system: standardized tolerancing (GD&T), statistical process control on dimensions, and modular product design all exist to guarantee interchangeability, and once guaranteed, it enables outsourced/multi-plant sourcing, field-replaceable spare-parts logistics, and the entire modern supply chain of independently produced components meeting at a common assembly point.
Total Quality Management is a company-wide management philosophy that makes continuous improvement of quality the responsibility of every employee and every process — not just an inspection department at the end of the line — built on customer focus, process thinking (Deming's PDCA cycle), fact-based decision making (statistical process control), and top-management commitment. Its significance is the shift it represents from "inspect quality in" (sorting good parts from bad after the fact, which only detects defects and wastes the cost already sunk into a bad unit) to "build quality in" (designing the process so defects are prevented at the source, per Crosby's "zero defects" and Deming's 14 points). TQM is also the philosophical ancestor of ISO 9001 quality-management-system certification and of Six Sigma's DMAIC methodology, and it reframes quality cost: the traditional view treats inspection and rework as necessary costs, while TQM treats the cost of poor quality (scrap, rework, warranty, lost customers) as far larger than the cost of prevention, making upfront investment in process capability and employee training the economically rational choice.
