23-Ind-A3 Facilities Planning · December 2015
Nivaar worked solution (AI-drafted; not reviewed by a licensed engineer)
National Exams — December 2015 — 98-Ind-A3 Facilities Design. Three-hour, closed-book exam (Casio or Sharp approved calculator only); any five of the seven questions constitute a complete paper and only the first five answered in the answer book are marked — all seven are solved below for completeness.
Reference texts: Tompkins, White, Bozer & Tanchoco, Facilities Planning (4th ed., Wiley) — the facilities-planning hierarchy, the facilities planning process, facility location and plant-site selection, manufacturing cells, machine space and line-balancing models, computerized layout algorithms (CRAFT/CORELAP), and material handling equipment/systems; Niebel & Freivalds, Methods, Standards, and Work Design (13th ed.) — assembly-line balancing (Ranked Positional Weight technique), balance delay, and production-quantity planning with scrap/rework.
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.
The facilities planning hierarchy places facilities planning as the physical-execution layer beneath an organization's corporate/business strategy, and decomposes it top-down into two parallel activities, one of which further decomposes into three specialist design activities. At the top, corporate/business strategy sets the mission, product/service line, and required capacity and service level the physical plant must support. Directly below it sits facilities planning itself, which splits into two co-equal streams: facility location — selecting the geographic region, community and specific site the facility will occupy (part iii) — and facility design — determining everything about the facility once its site is fixed. Facility design in turn decomposes into three specialist sub-activities that must be developed together: structural design (the building itself — construction type, external/architectural features, floor and bay layout constraints), layout design (the arrangement of all equipment, machinery and furnishings within the building envelope), and handling system design (the equipment and methods selected to move material, information and personnel between and within the departments the layout defines).
Every level below corporate strategy exists to serve the level above it, and the three facility-design sub-activities are not independent — the layout constrains and is constrained by the building's structural design (bay spacing, column locations, floor loading, clear height), and both are developed jointly with the handling system, since the handling equipment chosen (fixed conveyor vs. mobile AGV/forklift) determines the aisle widths, floor loading and overhead clearance the structural and layout designs must provide. This is why facilities planning is shown as a hierarchy rather than three unrelated tasks: a decision made at one level (e.g., a location with limited land area) constrains every level below it.
Facilities planning for a manufacturing facility follows an iterative, top-down process. The principal steps are:
1. Define/redefine the objectives. Establish the products and/or services to be produced, primary and support activities, and the performance criteria (cost, quality, delivery, flexibility) the facility must satisfy — derived directly from corporate strategy.
2. Specify the primary and support activities. Perform product, process and schedule design: determine what is to be produced, the processes/operations required, and the production schedule (quantities, timing) — the P-Q-R-S-T data (Product, Quantity, Routing, Supporting services, Timing) that every downstream step consumes.
3. Determine the interrelationships among all activities. Build the material-flow analysis (from–to chart of flow volumes) and the activity relationship (REL) chart capturing the qualitative closeness needs (shared personnel, supervision, safety, noise) between every pair of activities.
4. Determine the space requirements for all activities. Translate each activity/department's equipment, storage, and personnel needs into a required floor area, and compare against the space actually available on the chosen site (part iii).
5. Generate alternative facility plans. Using the relationship and space data, develop several candidate block layouts (and, where relevant, alternative locations) — manually or via a computerized layout algorithm (CRAFT/CORELAP, Question 4(ii)).
6. Evaluate the alternative facility plans. Score each alternative against the defined objectives (material handling cost, flexibility, capital cost, expandability, safety) using both quantitative measures ($\sum f_{ij}d_{ij}$, capital and operating cost) and qualitative judgment.
7. Select a facility plan. Choose the alternative that best satisfies the objectives, subject to budget, schedule and risk constraints.
8. Implement the facility plan. Detail-design, procure, construct/install, and commission the selected plan.
9. Maintain and adapt the facility plan. Because product mix, volumes and technology change continuously, the plan is periodically re-audited against current objectives and the process is re-entered at Step 1 whenever the facility no longer serves its objectives — facilities planning is a recurring cycle, not a one-time project.
Plant site selection is a facility-location decision (part i) with consequences that are expensive and slow to reverse once construction begins, so most site-selection failures trace back to a small set of recurring pitfalls rather than to any single bad data point:
Over-weighting a single quantitative factor. Choosing the site with the lowest land price, lowest construction cost, or largest tax incentive while treating everything else as secondary is the single most common pitfall — land and construction are a small fraction of a plant's total life-cycle cost, and a site that is cheap to build on but expensive to operate from (poor transportation access, thin labour pool, long inbound/outbound freight lanes) usually costs far more over the facility's life than the initial saving.
Ignoring total logistics cost in favour of proximity to one endpoint only. Selecting a site close to raw-material suppliers while ignoring finished-goods distribution cost (or vice versa) optimizes one leg of the supply chain and can inflate the other; the site decision should weigh inbound and outbound transportation cost together, not sequentially.
Underestimating labour availability, skill and cost. A community's current unemployment rate is a poor proxy for whether it can supply the specific skilled trades the plant needs; failing to survey the local/regional labour market in detail (skill mix, wage rates, competition from other employers, commuting patterns) risks a site that cannot be staffed at the assumed cost, or at all.
Treating temporary incentives as permanent cost advantages. Tax abatements, grants and utility-rate concessions are frequently time-limited (e.g., a 5–10 year abatement); building a site-selection decision around an incentive that expires long before the facility's planning horizon ends silently erodes the assumed cost advantage partway through the facility's life.
Insufficient site-specific technical verification. Relying on regional or municipal-level data without a proper geotechnical/soils investigation, floodplain and seismic check, and utility-capacity (power, water, wastewater) confirmation for the SPECIFIC parcel risks discovering foundation, drainage or utility-upgrade costs only after the site is already committed.
Ignoring expansion room and future flexibility. Sizing the site to only the initial facility footprint, with no allowance for the plant's own future growth (Question 1(ii), Step 9) or for adjacent land being sold to another party, can force a costly second-site decision within a few years of start-up.
Underestimating environmental, permitting and regulatory timelines. Environmental assessment, zoning approval and building-permit timelines vary widely by jurisdiction and can run far longer than a project schedule assumes; failing to confirm permitting requirements and realistic timelines before committing to a site is a frequent source of costly schedule slip.
Community and quality-of-life factors treated as an afterthought. A site with poor housing, schools, healthcare or amenities near the plant makes it harder to attract and retain the skilled staff and management the facility needs, particularly for specialized roles that must be recruited from outside the immediate area — this is easy to under-weight against purely economic factors, but drives turnover cost for years after start-up.
Political/regulatory instability and community attitude. A site in a jurisdiction with an unstable regulatory environment, or a community that is actively opposed to industrial development, risks delays, added compliance cost, or reputational damage that a purely economic site-comparison does not capture.
Failing to use a rigorous, weighted, multi-factor evaluation. The pitfalls above largely stem from the same root cause — comparing candidate sites informally or on one dominant factor rather than through a structured weighted factor-rating (or factor-comparison) analysis that explicitly scores every quantitative and qualitative factor and documents the trade-offs made.
