Lecture 11_Warehouse Management Flashcards
3 Options of Hub and Spoke system
-
direct transport
- central hub: cross-docking, separate dispatch and delivery
- decentral hub: cross-docking, separate dispatch and delivery
Withdrawal Strategies for Storage
- Fifo, Lifo, Shortes paths
Dedicated vs. Shared Capacity
Storage Strategies (EOQ Example)
Fixed vs. Flexible Warehouse Space
Assignment of storage location
Chaotic vs. Fixed Storage
Chaotic
- randomly
- closest free location
Fixed Storage location
- randomly
- maximum inventory
- popularity: # of orders including thi sproduct
- Cuber-per-order index (COI): ratio of max inventory to popularity
Formulate Mathematical Model of the Assignment of Storage location
Objective Function
Min ∑(i) ∑(j) x(ij) * b(i) * d(j) * c
Constraints
1. each product must be allocated to one bin:
∑(j) x(ij) = 1 ∀ i = 1,2,…,n
- at most one product can be assigned to one bin
∑(i) x(ij) <= 1 ∀ j = 1,2,…,m
x(ij) ∈ {0,1} ∀ i∈I, j∈J
i = product j = bin
Material flow system
Aspects
- Goods retrieval
- Putting of picked goods
- Automation
- Picking strategy
- Stages
Goods Retrieval
2 options
Man-to-goods
- distance minimization
- many order lines
- high quantities per order line
Goods-to-Man
- automation
- no travel time
Stages
Material FLow System
- Single stage
- Two stages with sorter
SKU
stock keeping unit
Picking
Retrieving of goods from warehouse and allocation of goods to orders
- demand < storage unit
- sort function
- separation: repplenishment zone, forward (picking) zone
Key Figures
* Mail Order Business
− 250,000 SKUs, 190,000 orders or 650,000 order lines/day
* Pharmaceutical wholesale
− 130,000 SKUs, 6,800 orders or 105,000 order lines/day
* Regional warehouse food retailer
− 8,150 SKUs, 780 orders, 300,000 order lines/day
Picking Strategies
3 items
1. Customer order based
* Storage location of the SKU
* Shortest paths, travelling salesman problem
* Sequential picking
2. Parallel Zoning
* Splitting of the customer order, merging
* Possibly higher picking performance, lower lead times
3. Simultaneous
* Batch picking
* Pro when: many orders, few SKUs
Picking Sequences
Common heuristics
4 items
* S-shaped
− Completely traverse all aisles that have a SKU to be picked
* Returner
− Turn around after the last position in each aisle
* Center line
− Completely traverse first and last aisle that has a SKU to be picked − Rest: in each aisle maximum until the middle
* Largest gap
− Completely traverse first and last aisle that has a SKU to be picked
− Rest: continue until reaching the largest gap (gap = distance cross aisle to storage location, storage location to
storage location)
Single Server
vs. Multiple Server
Queuing System
Single Server
- customers -single queue - single server
Multiple Server
- Customers - single queue - mutiple server
M/M/1
Queuing Theory
Arrival of customers
- arrival rate 𝜆 (expected # of customers per time unit)
- exponential distributed interarrival times (poisson process)
Service Process
- service rate µ (expected # of customers per time unit)
- exponential distributed service time
Singel server, no capacity restrictions, FIFO, customer discipline
Stability requirements 𝜆 < µ
Stability requirements M/M/n: 𝜆 < n * µ
Sequences of queues
Queuing Networks
- serial structure
- distributed structure
- aggregation
- loop structure
MTM vs. Queuing Models
MTM = Methods TIme Measurement
- breakdown of processes into sub-processes and evaluating by the average processing time
- e.g. zone picking = walking to bin, if necessary bending down, moving hand inside the bin, grabbin, if necessary raising up, putting, passing to the next picker
Average value of the process times (not stochastic)
