Trauma center moves to diversion status once all servers are busy (incoming patients are directed to other locations) Figure 7.1.: Process flow diagram.

Slides:



Advertisements
Similar presentations
Make to Stock (MTS) vs. Make to Order (MTO)
Advertisements

Waiting Line Management
Operations Management
OPSM 301: Operations Management Session 12: Service processes and flow variability Koç University Graduate School of Business MBA Program Zeynep Aksin.
3. 7 MBPF. Orange Juice Inc. produces and markets fruit juice
Capacity Setting and Queuing Theory
S. D. Deshmukh OM V. Capacity Planning in Services u Matching Supply and Demand u The Service Process u Performance Measures u Causes of Waiting u Economics.
MBA 8452 Systems and Operations Management
S. Chopra/Operations/Managing Services1 Operations Management: Capacity Management in Services Module u Why do queues build up? u Process attributes and.
1 ELEN 602 Lecture 8 Review of Last lecture –HDLC, PPP –TDM, FDM Today’s lecture –Wavelength Division Multiplexing –Statistical Multiplexing –Preliminary.
OM&PM/Class 7a1 Operations Management & Performance Modeling 1Operations Strategy 2Process Analysis 3Lean Operations 4Supply Chain Management 5Capacity.
Previously Optimization Probability Review Inventory Models Markov Decision Processes.
1 Part II Web Performance Modeling: basic concepts © 1998 Menascé & Almeida. All Rights Reserved.
Model Antrian By : Render, ect. Outline  Characteristics of a Waiting-Line System.  Arrival characteristics.  Waiting-Line characteristics.  Service.
IV. Little’s Law and Labor Costs
CSE 221: Probabilistic Analysis of Computer Systems Topics covered: Simple queuing models (Sec )
Managing Process Flows
Polling: Lower Waiting Time, Longer Processing Time (Perhaps)
The Theory of Queues Models of Waiting in line. Queuing Theory Basic model: Arrivals  Queue  Being Served  Done – Queuing theory lets you calculate:
CHAPTER 18 Waiting Lines.
Simulating Single server queuing models. Consider the following sequence of activities that each customer undergoes: 1.Customer arrives 2.Customer waits.
14-1. Copyright © 2006 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin 14 Capacity Planning and Queuing Models.
Queuing. Elements of Waiting Lines  Population –Source of customers Infinite or finite.
OM&PM/Class 6b1 1Operations Strategy 2Process Analysis 3Lean Operations 4Supply Chain Management 5Capacity Management in Services –Class 6b: Capacity Analysis.
Problem 8.4 K = ∞ R i = 60/4 = 15 /hr T p = 3 min = 0.05 hour c= 1 R p = c/Tp = 20 /hour Both Ti and Tp exponential Server $20 /hr Phone $5/hr Wait cost.
19-1 McGraw-Hill Ryerson Operations Management, 2 nd Canadian Edition, by Stevenson & Hojati Copyright © 2004 by The McGraw-Hill Companies, Inc. All rights.
Operating Processes process  A process is a set of tasks to be performed in a defined sequence  A process uses inputs to create outputs that are of value.
Capacity Management in Services Module
Model Antrian By : Render, ect. M/M/1 Example 2 Five copy machines break down at UM St. Louis per eight hour day on average. The average service time.
1 Part VI System-level Performance Models for the Web © 1998 Menascé & Almeida. All Rights Reserved.
Problem 3.4 MBPF A hospital emergency room (ER) is currently organized so that all patients register through an initial check-in process. At his or her.
Buffer or Suffer Principle
A Somewhat Odd Service Process (Chapters 1-6)
Queueing Theory Models Training Presentation By: Seth Randall.
1 Chapter 5 Flow Lines Types Issues in Design and Operation Models of Asynchronous Lines –Infinite or Finite Buffers Models of Synchronous (Indexing) Lines.
Introduction to Operations Research
Managing Processes and Capabilities CHAPTER THREE.
Process Analysis process  A process is a set of tasks to be performed in a defined sequence  Process analysis describes how a process is doing and can.
McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved. 18 Management of Management of Waiting Lines.
1 Queuing Systems (2). Queueing Models (Henry C. Co)2 Queuing Analysis Cost of service capacity Cost of customers waiting Cost Service capacity Total.
1 3. Process Flow Measures A hospital emergency room (ER) is currently organized so that all patients register through an initial check-in process. At.
MINGZHE HAN (CMP TUTOR) COMM 204 Review Session. Outline T ABLE OF C ONTENT (Basic Information) (Process Analysis) (Multiple Types and the Product Process.
Slide 1 Matching Supply with Demand: An Introduction to Operations Management Gérard Cachon ChristianTerwiesch All slides in this file are copyrighted.
Approximating the Performance of Call Centers with Queues using Loss Models Ph. Chevalier, J-Chr. Van den Schrieck Université catholique de Louvain.
Ó 1998 Menascé & Almeida. All Rights Reserved.1 Part VI System-level Performance Models for the Web (Book, Chapter 8)
Structure of a Waiting Line System Queuing theory is the study of waiting lines Four characteristics of a queuing system: –The manner in which customers.
Matching Supply with Demand: An Introduction to Operations Management Gérard Cachon ChristianTerwiesch All slides in this file are copyrighted by Gerard.
Dr. Anis Koubâa CS433 Modeling and Simulation
Adeyl Khan, Faculty, BBA, NSU Elements of Queuing System ArrivalsServiceWaiting line Exit Processing order System.
Ó 1998 Menascé & Almeida. All Rights Reserved.1 Part VI System-level Performance Models for the Web.
Lin/Operations/Managing Services1 Capacity Management in Services Module u Queuing processes and performance measures u Why do queues build up? u Performance.
WAITING LINES AND SIMULATION
Managing Flow Variability: Safety Capacity
ETM 607 – Spreadsheet Simulations
Results for p = 0.1 Graphs at different values of Call Arrival Rate for Call Blocking Probability (in %) System Utilization (Efficiency) (in %) Average.
Effect of Buffer Capacity
Demo on Queuing Concepts
IV-2 Manufacturing Systems modeling
How long must the plant operate on peak days?
Variability 8/24/04 Paul A. Jensen
Queuing Models and Capacity Planning
Waiting Lines Waiting lines are non-value added occurrences.
On average, there are 3(4.42) =13.26 claims waiting be processed.
Queuing Theory III.
Process Analysis “If you cannot describe what you are doing as a process, you do not know what you are doing.” W.E. Deming.
Queuing Theory III.
Queuing Theory III.
Effect of Buffer Capacity
Process design 2 – analysis
Presentation transcript:

Trauma center moves to diversion status once all servers are busy (incoming patients are directed to other locations) Figure 7.1.: Process flow diagram for trauma center 3 trauma bays

Figure 7.2.: Implied utilization vs probability of having all servers utilized Implied utilization Probability that all servers are utilized m=1 m=2 m=5 m=10 m= m=3

Figure 7.4.: Impact of waiting time on customer loss Average wait time [seconds] Fraction of customer lost

Inflow Figure 7.5.: A serial queuing system with three resources Outflow Outflow of resource 1 = Inflow of resource 2 UpstreamDownstream

Inflow Figure 7.6.: The concepts of blocking and starving Outflow Activity completed Outflow Resource is blocked Inflow Resource is starved Activity not yet completed Empty space for a flow unit Space for a flow unit with a flow unit in the space

Figure 7.7.: Flow rate compared at four configurations of a queuing system Sequential system, no buffers Cycle time=11.5 minutes Sequential system, one buffer space each Cycle time=10 minutes (1) Sequential system, unlimited buffers Cycle time=7 minutes; inventory “explodes” Horizontally pooled system Cycle time=19.5/3 minutes=6.5 minutes 6.5 min/unit7 min/unit6 min/unit 6.5 min/unit7 min/unit6 min/unit 6.5 min/unit7 min/unit6 min/unit 3 resources, 19.5 min/ unit each

Waiting problem Loss problem Pure waiting problem, all customers are perfectly patient. All customers enter the process, some leave due to their impatience Customers do not enter the process once buffer has reached a certain limit Customers are lost once all servers are busy Same if customers are patientSame if buffer size=0 Same if buffer size is extremely large Figure 7.8.: Different types of variability problems