Download
material handling and storage system n.
Skip this Video
Loading SlideShow in 5 Seconds..
Material Handling and Storage System PowerPoint Presentation
Download Presentation
Material Handling and Storage System

Material Handling and Storage System

1317 Vues Download Presentation
Télécharger la présentation

Material Handling and Storage System

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

  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.

  4. Equipment used as primary handling system

  5. Computer Control System Function performed by FMS computer control: • Workstation control. • Distribution of control instructions to workstations. • Production control. • Traffic control. - Primary handling system

  6. 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.

  7. Typical FMS performance reports

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. Quality Programs: SPC, TQM, 6, etc. Presenter: Mikell P. Groover MSE 438

  19. 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)

  20. 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

  21. 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

  22. 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

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

  24. 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

  25. 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

  26. Taguchi Loss Function • A loss occurs when a product’s 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

  27. 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

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

  29. 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

  30. 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

  31. Short History of Six Sigma • Started at Motorola in mid-1980s • Mikel Harry’s 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”

  32. 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)

  33. Sigma Value and Defect Rate Process sigmaDefect rateYield 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%

  34. Approach in Six Sigma • Management’s responsibility: • Identify key processes in the organization • Measure the effectiveness and efficiency of these processes • Initiate improvement in the worst performing processes

  35. 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

  36. 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

  37. 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

  38. 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

  39. 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

  40. 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