8. Warehousing, Storage and Material-Handling Systems

Introduction and Context

Warehousing is no longer viewed merely as the holding of inventory between production and distribution. In a contemporary production system, the warehouse is an operating system that synchronizes suppliers, manufacturing, customers, transport providers and information flows. Its design affects lead time, working capital, order accuracy, labour productivity, product quality, safety and customer service. A poorly designed warehouse can conceal production problems through excessive inventory, while a well-designed one can increase responsiveness without proportionately increasing cost.

For facilities planners, warehousing must therefore be considered together with plant layout, production scheduling, purchasing, packaging, transportation and information systems. The central question is not simply where material should be stored, but how material should flow through receiving, inspection, put-away, storage, replenishment, picking, packing, staging and dispatch. The appropriate solution depends on product characteristics, demand variability, unit-load structure, throughput, service requirements, available space, labour conditions, capital cost and the degree of automation justified by the operation.

This chapter develops a managerial and engineering framework for planning these activities. It examines storage policies, material-handling equipment, automation, performance measurement, safety, sustainability and implementation issues. The emphasis is on selecting an integrated system rather than choosing isolated equipment.

Learning Objectives

After studying this chapter, the student should be able to:

1. Explain the role and operating logic of warehouses in production and distribution systems.

2. Design the principal processes from receiving to dispatch.

3. Distinguish storage policies and select them according to demand, product and service conditions.

4. Apply unit-load, capacity, throughput and travel considerations to warehouse planning.

5. Compare conveyors, forklifts, cranes, automated storage and retrieval systems, robots, AGVs and AMRs.

6. Evaluate alternatives using cost, service, safety, flexibility, energy and information criteria.

7. Identify risks, governance requirements and implementation challenges in warehouse automation.

8. Use performance measures and applied analysis to improve warehouse operations.

The Warehouse as a Flow and Service System

A warehouse performs three related functions. First, it provides a temporal buffer between activities whose rates or schedules do not match. Second, it consolidates or breaks down material flows—for example, receiving full supplier pallets and shipping smaller customer orders. Third, it adds service value through inspection, labelling, kitting, postponement, sequencing and packaging.

The warehouse contains two interdependent systems. The physical system includes docks, aisles, racks, storage media, handling equipment, workstations and safety provisions. The information system identifies stock, locations, orders, priorities, tasks and status. A physically efficient warehouse with inaccurate information remains unreliable; conversely, an advanced warehouse-management system cannot compensate for excessive travel or unsafe layout.

A useful systems view separates four flows:

• Material flow: movement and transformation of products and components.
• Information flow: orders, receipts, locations, inventory records and task instructions.
• People flow: movement of operators, drivers, visitors and maintenance personnel.
• Resource flow: use of space, energy, equipment, packaging and working capital.

The design objective is to achieve the required service level with minimum total cost and acceptable operational risk. Total cost includes land and construction, storage equipment, handling equipment, labour, information technology, maintenance, energy, damage, inventory, errors, delays and the cost of lost flexibility. A low purchase price does not necessarily indicate an economical system.

Important Concepts and Terminology

A stock-keeping unit (SKU) is a distinct item identified for inventory control. An inventory location is a defined position in which a unit load or quantity of material may be placed. Throughput is the quantity of material processed per unit of time. Order cycle time is the elapsed time between order release and order completion or dispatch. Dock-to-stock time measures the interval from receipt at the dock until material is available in inventory.

A unit load is a quantity of material assembled for handling or storage as one entity, such as a pallet, tote, roll, carton or container. Cube utilization is the proportion of available three-dimensional storage volume occupied by inventory. Space utilization may also consider floor area, clearances, aisles and operational access. Slotting is the assignment of SKUs to storage or picking locations. Forward picking refers to a dedicated area from which customer orders are picked, supported by reserve storage. Cross-docking transfers goods from receiving to shipping with little or no storage.

Storage density describes the amount of inventory stored per unit of space. Accessibility is the ease and speed with which a particular load can be retrieved. Honeycombing occurs when empty spaces within storage positions cannot be used effectively. WMS denotes a warehouse-management system that controls inventory, locations, tasks and workflows. WCS, or warehouse-control system, coordinates automated equipment. AS/RS is an automated storage and retrieval system. AGVs follow defined routes or guidance systems, whereas AMRs use sensors and onboard software to navigate dynamically around obstacles.

From Receiving to Dispatch: Designing the Operating Process

Receiving and Inbound Control

Receiving begins before the vehicle arrives. Advance shipment information should identify the supplier, expected quantities, packaging, purchase order, lot or serial numbers and special handling requirements. Appointment scheduling reduces congestion and permits the warehouse to match dock capacity with labour and equipment availability.

At the dock, the process normally includes vehicle identification, document verification, unloading, count and condition inspection, barcode or radio-frequency identification capture, discrepancy recording and disposition. Materials may then move directly to production, quality quarantine, reserve storage, forward picking or cross-docking. The receiving area should be sized according to arrival variability, unloading rates and the maximum expected accumulation, not merely average daily volume.

Quality inspection must be integrated into the flow. If every item requires detailed inspection, a dedicated inspection zone may be appropriate. If inspection is sampling-based, material can proceed while status remains controlled in the information system. Unlabelled or unidentified material creates downstream errors and should not be allowed to enter available inventory.

Put-away and Storage

Put-away assigns received material to an appropriate location and physically moves it there. A location strategy should consider compatibility, dimensions, weight, environmental conditions, handling restrictions, demand frequency, replenishment requirements and future retrieval. Directed put-away—where the WMS recommends a location—generally performs better than informal placement, provided the master data are accurate.

Storage areas should distinguish reserve stock, forward pick stock, quarantine, damaged goods, returns, hazardous materials, value-sensitive items and staging inventory. Clear status identification prevents the serious error of treating physically present material as available material.

Picking and Replenishment

Picking is often the most labour-intensive warehouse activity. Its design begins with order profile analysis: lines per order, units per line, order frequency, SKU velocity, cube, weight, seasonality and required dispatch cut-off. Common methods include single-order picking, batch picking, zone picking and wave picking.

In single-order picking, one operator completes one order at a time. It is simple but may involve substantial travel. Batch picking groups similar orders so that one travel cycle collects several orders; sorting is then required. Zone picking assigns operators or equipment to specific zones, with orders moving between zones or being consolidated later. Wave picking releases work according to a planned time window, carrier departure, customer priority or production requirement.

Replenishment transfers stock from reserve storage to forward pick locations. It should be scheduled before pick faces become empty, but excessive replenishment increases handling and congestion. A practical control rule combines minimum and maximum quantities with demand variability and replenishment lead time.

Packing, Staging and Dispatch

Packing protects the product, facilitates handling, communicates information and influences transport cost. Packaging design should consider cube, strength, ergonomics, recyclability, product sensitivity and the possibility of standardizing cartons or containers. At the packing station, order verification may use barcode scanning, weight checks, vision systems or system-directed confirmation.

Dispatch staging organizes completed orders by route, carrier, customer, shipment time or production sequence. Staging lanes must be large enough to prevent mixing without becoming long-term storage. The dispatch process includes final verification, documentation, loading sequence, load restraint and electronic shipment confirmation. Poor staging discipline can negate accurate picking by causing misloads and missed departures.

Storage Policies and Slotting Decisions

Storage policy determines how locations are assigned and how much accessibility is sacrificed for density. In dedicated storage, each SKU has a reserved set of locations. This simplifies identification and replenishment but leaves unused space when stock is low. In random or shared storage, any suitable vacant location may be used. This improves space utilization but requires reliable location control and often increases search complexity.

Class-based storage combines the two approaches. Items are classified, often by demand frequency, value, cube or handling characteristics, and each class receives a defined area. Within the area, locations may be assigned dynamically. High-velocity items are placed near dispatch or at ergonomically favourable positions; slow-moving items occupy less accessible locations.

The familiar ABC classification is useful but incomplete. An item with low annual demand may have high criticality, hazardous properties, large cube or special service requirements. A more mature slotting process therefore considers multiple attributes:

• pick frequency and lines per day;
• replenishment frequency and reserve-to-forward relationship;
• cube, weight and dimensions;
• compatibility and environmental requirements;
• order correlation, such as products commonly purchased together;
• value, security and obsolescence risk; and
• ergonomic and legal constraints.

Slotting should be reviewed when demand patterns, packaging, product mix or order profiles change. A location that was optimal at the time of installation may become inefficient after a product launch or seasonal shift.

Unit Loads, Capacity and Throughput Analysis

Unit-load design is a foundational decision. Larger unit loads generally reduce handling touches and travel per unit, but they may reduce accessibility, increase equipment requirements and create higher damage risk. Smaller totes improve order flexibility but increase the number of movements. The selected unit load must be compatible with suppliers, production equipment, storage media, conveyors, vehicles and customers.

Capacity planning begins with inventory requirements rather than the number of racks that can fit in a building. For each SKU or product family, planners estimate maximum, average and safety stock; convert inventory into pallets, cartons, totes or other unit loads; and allow for growth, seasonal peaks, quarantine and operational staging. The calculation must distinguish storage capacity from operating capacity. A warehouse physically full of inventory cannot receive, pick or dispatch efficiently. Practical capacity is lower than nominal capacity because access, empty locations, safety clearances and workload variation must be preserved.

Throughput analysis asks how many loads or order lines must be processed per hour and in what time pattern. Average demand is insufficient when several trucks arrive together or when a dispatch cut-off creates a short peak. Equipment and workstations should be evaluated against peak or design-period demand, with an explicit allowance for variability.

Travel distance is a major driver of labour and equipment cost. A simple estimate of handling work is:

Handling work = number of trips × average travel distance × load or task factor.

More detailed analysis considers loaded and empty travel, vertical movement, acceleration, congestion, waiting and task interruption. From-to charts, spaghetti diagrams, discrete-event simulation and value-stream maps can reveal unnecessary movement. The best layout usually places high-frequency flows along short, direct routes while separating incompatible traffic.

Selecting Material-Handling Technologies

Equipment selection should follow a process and requirements analysis. The planner should define load characteristics, flow volume, destination pattern, travel distance, service time, accuracy, flexibility, environmental conditions, safety needs, staffing, maintainability and expected growth. Equipment should then be compared over its life cycle rather than on acquisition cost alone.

Conveyors

Conveyors provide continuous or intermittent movement along a defined path. Roller, belt, chain, overhead and flexible conveyors are common forms. They are suitable where flow is repetitive, destinations are stable and predictable movement justifies fixed infrastructure. Conveyors can support sorting, accumulation, scanning and connection between production and storage.

Their principal strengths are consistent flow, low direct labour for repetitive movement and integration with automated controls. Their weaknesses include route inflexibility, installation cost, space commitment and the possibility that a failure interrupts a large part of the system. Accumulation zones, bypasses and maintenance access are therefore important in conveyor design.

Forklifts and Industrial Trucks

Forklifts offer route flexibility and are effective for pallet movement, loading, unloading and variable destinations. Counterbalance, reach, turret, pallet and order-picker trucks serve different aisle and height conditions. Selection depends on load dimensions, lift height, aisle width, floor quality, battery or fuel arrangements and operator visibility.

Narrow aisles may increase storage density but require specialized trucks, accurate floor conditions and disciplined traffic control. Forklift planning must include pedestrian separation, speed control, charging areas, battery handling, visibility at intersections and inspection routines. A forklift is not simply a transport device; it is part of a safety-critical operating system.

Cranes and Automated Storage and Retrieval Systems

Stacker cranes serve high-bay storage and can place or retrieve unit loads with high positional accuracy. An AS/RS typically includes storage racks, a storage/retrieval machine, load-transfer devices, controls, identification technology and a supervisory software layer. Systems may be pallet-based, mini-load, shuttle-based or designed for trays, totes or specialized loads.

AS/RS can provide high density, controlled inventory, reduced travel and reliable operation in environments unsuitable for extensive manual handling. They require substantial capital, accurate master data, engineered interfaces and specialized maintenance. Their economic justification depends on sustained throughput, space cost, labour conditions, service requirements and the value of control—not merely on the desire to automate.

Robots, AGVs and AMRs

Robotic systems may perform palletizing, depalletizing, case handling, picking, induction, sorting or packing. AGVs operate along predefined routes, using magnetic, laser, reflectance or other guidance methods. AMRs use maps, sensors and software to select routes and respond to changing conditions. Both can reduce repetitive travel and improve traceability, but they require reliable load presentation, traffic rules, charging or battery strategy and exception handling.

Automation is most effective when the process is sufficiently stable and standardized. If product dimensions, destinations and procedures change continuously, flexible automation may be preferable to rigid automation. A human-automation design should specify which decisions remain with operators, how exceptions are escalated and how work continues during system downtime.

Information Systems, Analytics and Digital Control

A WMS maintains item, location, order, status and task information. It may interface with enterprise-resource-planning systems, transportation-management systems, labour-management systems, barcode scanners, RFID readers, voice terminals, robots and conveyor controls. The system should support receiving, directed put-away, replenishment, picking, cycle counting, packing, dispatch and performance reporting.

Data quality is a prerequisite. Dimensions, weights, barcodes, unit-of-measure conversions, storage constraints and order priorities must be accurate. A wrong carton dimension can cause slotting errors, conveyor jams or incorrect freight estimates. Cycle counting and exception reporting are therefore operational controls, not merely accounting exercises.

Analytics can identify travel patterns, congestion, missed cut-offs, replenishment failures, picker productivity, equipment utilization and order-error causes. Simulation is useful before construction or major automation because it tests alternative layouts and workload scenarios. Artificial intelligence may support demand forecasting, dynamic slotting, vision-based verification, predictive maintenance and robotic path planning. However, these applications should be governed by data quality, explainability, cybersecurity, human oversight and clear accountability.

Performance Measurement and Economic Evaluation

Warehouse performance should be measured as a balanced system. Useful indicators include:

• receiving dock-to-stock time;
• inventory record accuracy;
• storage utilization and honeycombing;
• order-picking accuracy and lines picked per labour hour;
• replenishment stockout frequency;
• order cycle time and on-time dispatch;
• equipment availability and utilization;
• damage, returns and safety incidents;
• energy use per unit handled; and
• cost per order, line, pallet or shipment.

No single measure is sufficient. Maximizing utilization can increase congestion; maximizing picker productivity can encourage unsafe speed; minimizing labour can produce excessive capital dependence. A service-level dashboard should therefore combine quality, speed, cost, safety, flexibility and sustainability.

Economic evaluation should include capital expenditure, installation, software, training, maintenance, energy, labour, facility changes, downtime during implementation, residual value and the cost of failure. Payback period is easy to communicate but may ignore long-term benefits and risk. Net present value, internal rate of return, sensitivity analysis and scenario analysis provide a stronger basis for major investments. Scenarios should test demand growth, product-mix change, labour cost, peak volume, equipment downtime and expansion requirements.

Safety, Governance and Sustainability

Warehouse safety includes traffic management, pedestrian protection, rack integrity, load stability, machine guarding, ergonomic design, fire protection, emergency access, battery charging, hazardous-material control and operator competence. Risk assessment should be conducted during layout design, not after commissioning. Intersections, blind corners and shared workspaces deserve particular attention.

Governance requires clear ownership of inventory status, access rights, master data, system changes, maintenance records and incident investigation. Automated systems introduce cybersecurity risks because warehouse controls may be connected to enterprise networks and external service providers. Access should be role-based, changes logged, backups tested and recovery procedures rehearsed.

Sustainability extends beyond energy-efficient equipment. It includes reduced travel, right-sized packaging, reusable containers, repairable equipment, efficient lighting, battery-life management, lower damage and appropriate reverse logistics. A dense automated system may reduce building footprint but increase embodied energy and dependence on specialized components. Decisions should therefore use a life-cycle perspective.

Applied Case: Redesigning a Mixed-Model Components Warehouse

Background

The following is an illustrative case. Meridian Components supplies electrical and mechanical parts to an assembly plant producing several product variants. Its warehouse occupies 6,000 square metres and receives approximately 180 pallets per day. The warehouse supplies production lines through hourly milk runs and also ships service parts to external customers.

Situation and Problem

The existing layout had receiving and dispatch on opposite sides, reserve pallets stored in fixed SKU locations, and production-picking aisles arranged without reference to demand frequency. Operators reported long travel distances, frequent replenishment interruptions and congestion at the production issue area. Inventory records were generally reliable, but urgent orders were often staged in the wrong lane. Management was considering a high-cost AS/RS without first examining process design.

Analysis

A six-week study classified SKUs by pick frequency, cube, criticality and order correlation. Twenty percent of SKUs generated approximately 70 percent of production pick lines, while several low-volume parts were critical to assembly continuity. The study found that high-frequency parts were located in reserve racks far from the production issue point. Fixed storage also created empty positions during low-stock periods. A spaghetti analysis showed that operators travelled repeatedly between receiving, reserve storage and forward pick areas. Peak workload occurred during the two hours before production milk runs, not evenly throughout the shift.

Approach and Solution

The redesign used a hybrid policy. High-frequency, small parts were placed in a forward-pick zone close to production staging, with reserve stock in shared locations. Critical low-volume parts received dedicated, visually controlled locations. Palletized components were assigned to a class-based reserve area. A one-directional material route reduced cross-traffic, while pedestrian lanes and forklift crossings were physically marked.

The receiving process introduced advance shipment information, barcode verification and directed put-away. Replenishment triggers were linked to production schedules and minimum forward quantities. A batch-picking method was introduced for service orders, while production kits were picked by zone and consolidated at a controlled staging point. Dispatch lanes were labelled by route and cut-off time, and the WMS prevented shipment confirmation until scan verification was complete.

Rather than immediately installing an AS/RS, management piloted AMRs for repetitive movement between reserve storage and production staging. The pilot included manual fallback procedures, charging locations, traffic rules and an exception-management process. A later investment decision was made contingent on measured peak throughput and the stability of the product mix.

Outcome

The redesigned system reduced unnecessary travel, improved visibility of urgent material and separated production staging from external dispatch. The most important improvement came from slotting and process control rather than from a single technology purchase. The pilot also showed that AMRs were useful for predictable pallet transfers but not for irregular, damaged or poorly labelled loads.

Learning Points

1. Warehouse automation should follow process analysis, not replace it.

2. ABC analysis should be supplemented by criticality, cube, correlation and handling constraints.

3. Peak workload and dispatch windows are more informative than daily averages.

4. A hybrid storage and handling system can provide better flexibility than a uniform technology choice.

5. Exception handling, fallback procedures and data quality determine real automation performance.

Common Challenges and Professional Mistakes

A frequent mistake is designing storage capacity from average inventory while ignoring seasonal peaks and staging requirements. Another is maximizing rack density at the expense of accessibility, replenishment and fire safety. Treating all SKUs alike leads to poor slotting, while using ABC classification mechanically can misplace critical items.

Other recurring problems include inadequate dock scheduling, unclear inventory status, poor carton standardization, unprotected pedestrian routes, insufficient maintenance access, underestimation of software integration effort and failure to test exception cases. Automation projects may also underestimate change-management needs. Operators must be involved in process design, training and acceptance testing because they understand variations that formal process maps often omit.

A warehouse should not be evaluated only by utilization or labour reduction. A system that is highly utilized but unable to absorb a peak, recover from a failure or accommodate a new product may be economically weak. Professional judgment requires explicit trade-offs among cost, service, safety, resilience and future adaptability.

Current Developments and Best Practices

Warehouse systems are increasingly characterized by modular automation, mobile robotics, goods-to-person picking, real-time location data, computer vision, digital twins and energy-aware controls. These developments reduce the need for fixed infrastructure in some applications, but they also increase dependence on software, connectivity and skilled maintenance.

Best practice is to begin with a clearly defined operating model and measurable requirements. Establish accurate item and location data; design unit loads jointly with suppliers and production; separate people and vehicles; use slotting based on actual order profiles; size for peak conditions; provide controlled staging; test information-system interfaces; and introduce automation in scalable modules. Before full deployment, conduct simulation, pilot testing, safety validation, failure-mode analysis and operator training. Finally, review performance after implementation because actual demand and behaviour will differ from the original design assumptions.

Chapter Summary

Warehousing is an integrated flow system linking receiving, storage, production supply, picking, packing and dispatch. Effective design balances space, accessibility, throughput, service, safety, information accuracy and total life-cycle cost. Storage policies range from dedicated and random storage to class-based and hybrid approaches. Slotting should consider velocity as well as cube, criticality, correlation, compatibility and ergonomics.

Unit-load design and capacity analysis provide the basis for selecting storage media and handling equipment. Conveyors suit stable, repetitive flows; forklifts provide flexibility; cranes and AS/RS support dense, controlled storage; and robots, AGVs and AMRs address selected repetitive or variable movements. Technology must be matched to process stability and data quality. WMS and related digital systems coordinate physical activity, while analytics and simulation support planning and improvement.

The central managerial lesson is that warehouse performance comes from integration. Layout, policy, equipment, information, people, safety and governance must be designed together. Automation is valuable when it solves a defined operational problem and is supported by reliable data, maintenance, exception handling and appropriate economic analysis.

Key Terms

AS/RS: Automated storage and retrieval system that places and retrieves loads under computer control.

AGV: Automated guided vehicle that follows predefined guidance or routes.

AMR: Autonomous mobile robot that navigates dynamically using sensors and software.

Batch picking: Picking method in which items for several orders are collected during one travel cycle.

Class-based storage: Storage policy assigning groups of items to designated areas according to selected characteristics.

Cross-docking: Movement of received goods to dispatch with minimal intervening storage.

Cube utilization: Proportion of available storage volume occupied by inventory.

Dedicated storage: Policy in which each SKU has reserved storage locations.

Forward picking: Picking from a readily accessible area replenished from reserve storage.

Honeycombing: Loss of usable capacity caused by inaccessible or stranded empty spaces.

Order cycle time: Time from order release to order completion or dispatch.

Random storage: Policy in which inventory is placed in any suitable available location.

Slotting: Assignment of products to storage or picking locations.

Throughput: Quantity of material processed by a system during a specified period.

Unit load: Quantity of material handled as one entity.

WCS: Warehouse-control system coordinating automated equipment and controls.

WMS: Warehouse-management system controlling inventory, locations, tasks and workflows.

Zone picking: Method assigning different warehouse areas to different operators or equipment.

Review Questions

Short Answer Questions

1. Why should warehouse design consider material, information, people and resource flows together?

2. Distinguish storage capacity from operating capacity.

3. What is the purpose of forward picking and replenishment?

4. State two situations in which conveyors may be preferable to forklifts.

5. Why is ABC classification insufficient as the sole basis for slotting?

Long Answer Questions

1. Explain the complete warehouse process from receiving through dispatch and identify the principal control points.

2. Compare dedicated, random, class-based and hybrid storage policies, including their effects on accessibility and space utilization.

3. Discuss the factors that should guide selection among forklifts, conveyors, cranes, AS/RS, AGVs and AMRs.

4. Develop a framework for evaluating a warehouse automation proposal using operational, financial, safety and strategic criteria.

5. Explain how WMS, WCS, analytics and simulation contribute to warehouse performance and governance.

Analytical / Application Questions

1. A warehouse has high average capacity utilization but frequent congestion during the final two hours before dispatch. Diagnose the likely causes and recommend a measurement and redesign approach.

2. A company must choose between a high-density AS/RS and a flexible AMR system for a product mix with uncertain demand and frequent packaging changes. Analyze the trade-offs and state the additional data required.

3. Design a slotting policy for a warehouse containing high-frequency standard parts, low-volume critical parts, hazardous materials and bulky seasonal products. Justify the location, handling and control rules for each category.

22. Multiple Choice Questions with Answers

Question 1

Which design decision most directly balances handling efficiency with accessibility to inventory?

A. Selecting the largest possible unit load for every SKU

B. Designing unit loads and storage policies according to demand, product and retrieval requirements

C. Maximizing rack height regardless of equipment capability

D. Assigning every SKU a dedicated location

Correct Answer: B. Designing unit loads and storage policies according to demand, product and retrieval requirements

Question 2

A warehouse uses a forward-picking area replenished from reserve storage. What is the principal purpose of this arrangement?

A. To eliminate the need for inventory records

B. To place all inventory at the dispatch dock

C. To reduce picking travel while retaining reserve capacity

D. To ensure that every SKU is stored in a fixed location

Correct Answer: C. To reduce picking travel while retaining reserve capacity

Question 3

Which situation is most suitable for a conveyor system?

A. Highly variable destinations and frequent route changes

B. Stable, repetitive movement along a defined path

C. Outdoor movement across changing terrain

D. Irregular handling of damaged loads

Correct Answer: B. Stable, repetitive movement along a defined path

Question 4

Why can maximizing warehouse cube utilization reduce operational performance?

A. It always increases product damage

B. It can reduce accessibility, increase congestion and leave insufficient operating space

C. It prevents the use of barcode systems

D. It eliminates the need for reserve storage

Correct Answer: B. It can reduce accessibility, increase congestion and leave insufficient operating space

Question 5

Which additional factor is most important when slotting low-volume components?

A. Only annual demand

B. Only carton colour

C. Criticality, compatibility and handling constraints

D. Distance from the employee entrance only

Correct Answer: C. Criticality, compatibility and handling constraints

Question 6

A warehouse experiences severe workload peaks before production milk runs. Which planning approach is most appropriate?

A. Use only average daily throughput

B. Size labour and equipment for the relevant peak and test variability

C. Ignore staging because it is not storage

D. Increase storage density without measuring flow

Correct Answer: B. Size labour and equipment for the relevant peak and test variability

Question 7

What is a key distinction between an AGV and an AMR?

A. An AGV carries loads but an AMR cannot

B. An AGV generally follows predefined guidance, while an AMR navigates dynamically

C. An AMR always requires a conveyor

D. An AGV is used only for external transportation

Correct Answer: B. An AGV generally follows predefined guidance, while an AMR navigates dynamically

Question 8

Which condition most strongly supports postponing an AS/RS investment?

A. Stable high-volume flow and high space cost

B. Accurate master data and predictable unit loads

C. Uncertain demand, frequent packaging changes and poorly defined processes

D. A requirement for controlled high-density storage

Correct Answer: C. Uncertain demand, frequent packaging changes and poorly defined processes

Question 9

What is the principal function of a WMS in the warehouse described in the chapter?

A. Replacing all physical handling equipment

B. Controlling inventory, locations, tasks and workflow information

C. Determining product selling prices

D. Providing electrical power to automated equipment

Correct Answer: B. Controlling inventory, locations, tasks and workflow information

Question 10

In the illustrative case, which intervention produced the most fundamental improvement before major automation?

A. Installing the tallest possible racks

B. Replacing all forklifts with robots immediately

C. Improving slotting, process control, staging and directed put-away

D. Eliminating reserve storage

Correct Answer: C. Improving slotting, process control, staging and directed put-away