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Material Handling and Storage System

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Title: Material Handling and Storage System


1
Material Handling and Storage System
  • Functions of the Handling System
  • Random, independent movement of workparts between
    stations.
  • Handle a variety of workpart configurations.
  • Temporary storage.
  • Convenient access for loading and unloading
    workparts.
  • Compatible with computer control.

2
FMS Layout Configurations
  • In-line layout
  • Loop layout
  • Ladder layout
  • Open field layout
  • Robot-centered cell

3
Material Handling Equipment
The material handling function in a FMS is often
shared between two systems
  • Primary handling system - establishes the basic
    layout of the FMS and is responsible for moving
    workparts between stations in the system.
  • Secondary handling system - consists of transfer
    devices, automatic pallet changers, and similar
    mechanisms located at the workstations in the FMS.

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Equipment used as primary handling system
10
Computer Control System
  • Function performed by FMS computer control
  • Workstation control.
  • Distribution of control instructions to
    workstations.
  • Production control.
  • Traffic control. - Primary handling system

11
Function performed by FMS computer control
  • Shuttle control. Secondary handling system
  • Workpiece monitoring.
  • Tool control. - concerned with managing two
    aspects of the cutting tools (a) tool location,
    (b) tool life monitoring.
  • Performance monitoring and reporting - see table.
  • Diagnostics.

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Typical FMS performance reports
14
Human Resources
Humans are needed to manage the operations of the
FMS. Functions typically performed by humans
  • Loading raw workparts onto the system
  • Unloading finished parts (or assemblies) from the
    system
  • Changing and setting tools
  • Equipment maintenance and repair
  • NC part programming in a machining system
  • Programming and operating the computer system
  • Overall management of the system.

15
FMS Benefits
  • Increased machine utilization.
  • FMSs achieve a higher average utilization than
    stand-alone machines in a conventional machine
    shop. Reasons include (1) 24 hour per day
    operation, (2) automatic tool changing at machine
    tools, (3) automatic pallet changing at
    workstations, (4) queues of parts at stations,
    and (5) dynamic scheduling of production that
    takes into account irregularities from normal
    operations. It should be possible to approach
    80 to 90 asset utilization.

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  • Fewer machines required. Because of higher
    machine utilization.
  • Reduction in factory floor space required.
    Compared to a job shop of equivalent capacity, a
    FMS generally requires less floor area.
    Reductions in floor space requirements 40 to
    50.
  • Greater responsiveness to change. A FMS improves
    response capability to part design changes,
    introduction of new parts, changes in production
    schedule and product mix, machine breakdowns, and
    tool failures. Adjustments can be made in the
    production schedule from one day to the next to
    respond to rush orders and special customer
    requests.

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  • Reduced inventory requirements. Because
    different parts are processed together rather
    than separately in batches, WIP is less than in
    batch production. Inventories of starting and
    finished parts reduced also. Reductions 60 to
    80.
  • Lower manufacturing lead times. Closely
    correlated with lower WIP is MLT. This means
    faster customer deliveries.
  • Reduced direct labor requirements and higher
    labor productivity. Savings 30 to 50
  • Opportunity for unattended production.

18
FMS Planning and Design Issues
  • Part family considerations.
  • The part family that will be processed on the
    FMS must be defined. Part families can be based
    on product commonality as well as part
    similarity. The term product commonality refers
    to different components used on the same product.
  • Processing requirements.
  • In machining applications, nonrotational parts
    are produced by machining centers, milling
    machines, and like machine tools rotational
    parts are machined by turning centers and similar
    equipment.

19
FMS Planning and Design Issues(continued)
  • Physical characteristics of the workparts.
  • Part sizes and weights determine the size of
    the machines and the size of the material
    handling system.
  • Production volume.
  • The production quantities determine how many
    machines will be required. Production volume is
    also a factor in selecting the most appropriate
    type of material handling equipment for the
    system.

20
FMS Planning and Design Issues(continued)
  • Variations in process routings. If variations in
    process sequence are minimal, then an in-line
    flow is most appropriate. As product variety
    increases, a loop is more suitable. If there is
    significant variation in the processing, a ladder
    layout or open field layout are most appropriate.
  • Work-in-process and storage capacity. If WIP is
    too low, then stations may become starved. If
    WIP is too high, then congestion may result. The
    WIP level should be planned.

21
FMS Planning and Design Issues(continued)
  • Pallet fixtures. The number of pallet fixtures
    required in the system must be decided. Factors
    include levels of WIP allowed in the system, and
    differences in part style and size. Parts that
    differ too much require different fixturing.
    Consider modular fixturing.
  • Tooling. Tooling decisions include types and
    numbers of tooling at each station.
    Consideration should also be given to the degree
    of duplication of tooling at the different
    stations. Tool duplication tends to increase
    routing flexibility.

22
FMS Operational Issues
  • Scheduling and dispatching.
  • Scheduling of production dictated by the
    master production schedule. Dispatching
    launching of parts into the system at the
    appropriate times.
  • Machine loading.
  • Allocating operations and tooling resources
    among the machines in the system to accomplish
    the required schedule.
  • Part routing.
  • Selecting routes to be followed by each part
    in the production mix so as to maximize use of
    workstation resources.

23
FMS Operational Issues
  • Part grouping.
  • Selecting groups of part types for
    simultaneous production, given limitations on
    available tooling and other station resources.
  • Tool management.
  • Managing available tools includes decisions on
    when to change tools, allocation of tools to
    stations, and similar issues.
  • Pallet and fixture allocation.
  • Allocation of pallets and fixtures to parts in
    the system.

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Quality Programs SPC, TQM, 6?, etc.
  • Presenter Mikell P. Groover
  • MSE 438

28
SPC, TQM, and 6?
  • SPC Statistical Process Control
  • TQM Total Quality Management
  • 6? Six Sigma
  • Other terms associated with quality
  • QC Quality Control (Traditional)
  • QA Quality Assurance
  • QE Quality Engineering (Taguchi)

29
Traditional Quality Control
  • Focus on inspection detecting poor quality and
    taking corrective action to eliminate it
  • Attention on sampling and statistical methods
  • Principal tools in statistical quality control
  • Control charts
  • Acceptance sampling

30
Quality Assurance
  • Broader scope of activities than quality control
  • Not just the inspection department
  • Attempts to ensure that a product or service will
    satisfy (or surpass) the requirements of the
    customer

31
Total Quality Management
  • A management approach that pursues three main
    objectives
  • Achieving customer satisfaction
  • Internal and external customers
  • Importance of product design
  • Continuous improvement
  • Encouraging involvement of the entire workforce

32
Quality Engineering (Taguchi)
  • Broad range of engineering and operational
    activities whose aim is to ensure that a
    products quality characteristics are at their
    nominal or target values
  • Robust design
  • Taguchi loss function
  • QE overlaps with TQM

33
Robust Design
  • A product or process design in which the function
    and performance is relatively insensitive to
    variations (noise factors)
  • Unit-to-unit variations - inherent random
    variations in materials, machinery, etc.
  • Internal variations wear, fatigues of metals
    parts, operational errors, etc.
  • External variations outside temperature,
    humidity, input voltage

34
Examples of Robust Design
  • Product
  • A car that starts in Minneapolis in January as
    well as in Tucson in July
  • A tennis racket that returns the ball as well
    when hit near the rim as when hit in dead center
  • Process
  • A metal forging operation that presses good parts
    despite variations in temperature of the starting
    billet

35
Taguchi Loss Function
  • A loss occurs when a products functional
    characteristics differ from their nominal or
    target values
  • The loss increases at an accelerating rate as the
    deviation grows, according to Taguchi
  • Loss function expressed mathematically
  • L(x) k(x N)2

36
Statistical Process Control
  • Involves the use of various methods to measure
    and analyze a process
  • Applicable in both manufacturing and service
    operations
  • Objectives
  • Improve quality of process output
  • Reduce process variability and achieve process
    stability
  • Solve processing problems

37
Seven Tools in SPC
  • Control charts
  • Histograms
  • Pareto charts
  • Check sheets
  • Defect concentration diagrams
  • Scatter diagrams
  • Cause and effect diagrams

38
Elements of Successful SPC
  • Management commitment and leadership
  • Team approach to problem solving
  • SPC training for all employees
  • Emphasis on continuous improvement
  • A recognition and communication system

39
Six Sigma
  • Quality management approach to improve
    effectiveness and efficiency of processes
  • Team approach to improvement projects
  • Goals of Six Sigma
  • Reduce defects
  • Reduce variance
  • Improve process capability
  • Support continuous improvement

40
Short History of Six Sigma
  • Started at Motorola in mid-1980s
  • Mikel Harrys study of process variation
  • Supported by CEO Robert Galvin
  • Launched at Allied Signal in early 1990s
  • Launched at General Electric in 1995
  • Jack Welch called it the most challenging and
    potentially rewarding initiative we have ever
    undertaken at GE

41
What is a Sigma?
  • Sigma (?) refers to the standard deviation of a
    probability distribution
  • It is a measure of the variation or spread about
    the mean of the distribution
  • Usually refers to a Normal distribution
    (bell-shaped)

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Sigma Value and Defect Rate
  • Process sigma Defect rate Yield
  • 1? 691,462 pm 30.9
  • 2? 308,538 pm 69.1
  • 3? 66,807 pm 93.3
  • 4? 6,210 pm 99.4
  • 5? 233 pm 99.98
  • 6? 3.4 pm 99.99966

44
Approach in Six Sigma
  • Managements responsibility
  • Identify key processes in the organization
  • Measure the effectiveness and efficiency of these
    processes
  • Initiate improvement in the worst performing
    processes

45
Some Definitions
  • Process a series of steps or activities that
    take inputs, add value, and produce an output
  • Effectiveness measure of how well customer
    requirements are met or exceeded
  • Efficiency measure of how well resources are
    utilized to achieve effectiveness

46
Five Steps in Six Sigma
  • DMAIC
  • Define the problem
  • Measure the process
  • Analyze the process
  • Improve the process
  • Control implement control over the new or
    improved process

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1. Define
  • Charter
  • Business case why the project should be
    accomplished
  • Problem statement
  • Goals and objectives
  • Milestones measures of progress
  • Roles and responsibilities of team members

48
Define (continued)
  • Identify customer needs and requirements
  • Customer recipient of product or service of the
    process to be improved
  • Create high-level process map
  • Process map flow graph showing the steps and
    decision points in the process

49
2. Measure
  • Creation of the Data Collection Plan
  • Where measurement should occur
  • Input measures (supplier effectiveness)
  • Process measures (your efficiency)
  • Output measures (your effectiveness)
  • Types of data
  • Discrete data binary (on/off), counts
  • Continuous data quantitative over time

50
Measure (continued)
  • Implementation of the data collection plan
  • Collect the data
  • Determine baseline sigma of current process
  • Calculate defects per million
  • Find corresponding sigma level

51
Example Food delivery
  • Possible defects (1) not on time, (2) order
    incorrect, (3) not fresh
  • In 50 deliveries, 13 were not in time, 3 were
    incorrect, and none were not fresh
  • DPM D/NC x 1,000,000
  • DPM defects per million, D defects (13 3
    0), N no. of units (50 deliveries), C no. of
    defect categories (3)
  • DPM 16(50x3) x 1,000,000 106,667
  • Current sigma level about 2.75
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