Home Products News Other Info Ordering Company

Home

 FastFact Inputs, Outputs, Scrap & Rework
 FastFact Inputs, Outputs, Scrap & Rework


FastFact Accurately Monitors Material Inputs, Production Outputs, Scrap & Rework

  Get a Handle on Inputs & Outputs

Effective management requires accurate and timely knowledge of material inputs, product outputs, and in-process losses at each stage of processing.  FastFact makes it possible to conveniently and accurately collect this information.

There are specialized channels dedicated to measuring inputs (raw materials, components, assemblies, etc.), outputs (pieces, parts, finished goods, etc.), scrap, and rework.  These direct measurements are supplemented by user interface entries and pre-defined formulas.  The bottom line is FastFact can provide excellent information to production planners, cost accountants, and managers, while simultaneously keeping supervisors and operators alerted to problems and exceptions.

Prior to a job being tracked by FastFact, raw materials and their use factors, along with product outputs and their expected yields, are loaded into the system using the Job Scheduler.  Associations between various channels and inputs and outputs are also defined.  After a job is started, the inputs and outputs are measured by sensing transducer readings and transforming the raw data into meaningful information. If data can’t be sensed directly, it can frequently be inferred from an input channel that is sensed. For example, using a counter that counts press strokes, one stroke may also be used to count two output parts and/or tally one pound of steel.

The Inputs Tab and Outputs Tab summarize a wide variety of information, by machine or process, by shift and job, and by individual resource type.  For each input resource, the following values are maintained in near real-time:

  • Input Type (raw material, component, sub-assembly)
  • Input Name
  • Input Total
  • Input Scrapped
  • Weighted Input per Cycle

For each output category, the following values are maintained:

  • Output Name
  • Total Output
  • Scrapped Output
  • Good Output
  • Reworked Output


Scrap & Rejects Constantly Monitored & Classified

For each input resource or output type, independent scrap tallies are maintained for the current job and current shift. Reasons for the scrap are user-defined, as are the units of measure. There may be as many scrap reasons defined as required to clearly identify all the causes or symptoms of problems. Each input or output may have a dollar value associated with its “good” value and its scrap value. This allows various types of scrap losses to be expressed in a common unit of measure.

Scrap or rework can be automatically tallied and classified using dedicated channels. When a job is defined, an association is made between the channel and the input or output identifier and the scrap reason.

Scrap and rework can also be manually entered at any workstation connected to the FMU. Entering scrap is simply a matter of selecting what is to be scrapped and entering the quantity. FastFact supports the definition of multiple units of measure for each raw material or part. This allows entries to be made in customary units.

 
 


 

 
  The Scrap Tab of the Real-Time Display presents information in grid form and using bar charts. User selections allow information sorted, grouped, filtered, and the column order changed. Separate current shift and current job information is maintained and updated every few seconds.

For each input and output scrap category, the following information is maintained in near real-time:
  • Scrap category or reason
  • Total Scrap Quantity (measured, sensed, & entered)
  • Scrap Quantity from Rework (output scrap only)
  • Reclassified Scrap Quantity from Good (output only)
 
   

 

Home
Up
Plant Diagram
Hardware
User Interface
Resources
Acquisition Intro
Cycle Times & Rates
Profile Analysis
SPC
Measurements
OEE
Plant Floor
Downtime & State
Inputs, Outputs, Scrap
Labor Time
Web Reports
Job Scheduling
 
 

Copyright © 2005 - All Rights Reserved
InFact Data Corporation