Integral Logistics Management — Operations Management and Supply Chain Management Within and Across Companies

15.3 Order Monitoring and Shop Floor Data Collection

Intended learning outcomes: Describe recording issues of goods from stock and completed operations. Produce an overview on progress checking, quality control, report of order termination, and automatic and rough-cut data collection.

Shop floor data collection provides for the reporting of all events relevant to planning and accounting during the value-added chain.

From thisfeedback, the exact state of orders can be derived, so that shop floor data collection additionally serves order monitoring and order checking as well as order coordination among orders that belong together in sales and distribution, R&D, production, and procurement.

15.3.1 Recording Issues of Goods from Stock

From central warehouses, goods may be withdrawn only upon presentation of a parts requisition or a picking list. The data that appear on a parts requisition should include

  • Order ID and order position
  • Item ID
  • Reserved quantity in stock units
  • Reserved quantity in picking units. For example, an item may be carried in stock in kilos, but picked in meters (for example, materials in bars) or in number of sheets (sheet metal). The factor required for this conversion is maintained as an attribute of the bill-of-material position or, if it is the same for every possible issuance, as an attribute of the item master data.

For unplanned issuances, the parts requisition must be filled out in its entirety.[note 1508] An availability check must precede every unplanned issuance, so that already confirmed reservations of physically available warehouse stocks for other orders can be taken into account (see Section 12.1).

For planned issuances from stock, the data that have to be collected are limited to the actually issued quantity, recorded either in converted units or in stock units. If the issued quantity corresponds to the reserved quantity, the only fact reported is that the material was “issued.”

For a picking list, in a first step only those positions for which the issued quantity differs from the reserved quantity are recorded. Then the so-called backflush technique is used:

The backflush technique reports the picking list itself as “issued,” whereby every (remaining) position on it is reported as issued in the reserved (or produced) quantity.[note 1509]

A critical point backflush technique is a backflush technique performed at a specific point in the manufacturing process, at a critical operation, or at an operation where key components are consumed ([APIC16]). 

15.3.2 Recording Completed Operations

Among the data that are printed on an operation card are

  • Order ID and order position
  • ID of the assigned work center
  • ID of the assigned machine or tool
  • Quantity to be processed
  • Standard setup load
  • Standard run load
  • If needed, the quantity to be produced in a unit that differs from the one on the order. For example, orders may be for pieces, but production is in meters (for sheet metal trimming, for example). The necessary conversion factor is an attribute of the operation object.

If the execution matches the standard, the only recorded fact is the execution of the operation. By collecting the number of finished items and the number of produced scrap items, rated capacity can be compared with demonstrated capacity.

Demonstrated capacity is proven capacity calculated from actual performance data, usually ex­pressed as the average number of items produced by the standard load hours per item ([APIC16]).

Furthermore, actual operationload, measured in capacity units, can be collected, as well as effective times. Standard operation time can then be compared with actual operation time. In addition, downtime might be of interest:

Downtime is time when a resource is scheduled for operation but is not producing for reasons such as maintenance, repair, or setup ([APIC16]).

For statistical and accounting purposes, the ID of the worker goes on record. In multiperson servicing, various operation cards are recorded, all referring to the same operation. If the work center or other planning data change during the execution of the job, the altered data must be registered. The order ID is also recorded for every unplanned executed operation.

Also conceivable is a separate recording of the actual quantities and the fact that the operation was completed. This may be necessary because of the legal situation (labor unions). In this case, recording includes only the number of produced items (good items and scrap) on the operation card. Separate collection documents then keep note of the actual loads. These summarize the activity of the personnel along with their other activities (training, illness, vacation, and so on).

15.3.3 Progress Checking, Quality Control, and Report of Order Termination

Progress checking monitors the execution of all work, in terms of quantity and delivery reliability, according to a plan.

Progress checking allows determination of the position of a production order in process at a specific moment. Every time a parts requisition or operation card is reported, the administrative status of the position changes into “issued” or “executed.” A strictly maintained reporting system is the prerequisite for exact control. It is important to report every operation as “executed” immediately upon completion. This ultimately serves for order coordination. In turn, the meaningfulness of scheduling and capacity planning is maintained. The system is transparent and finds acceptance with the users.

The recorded actual load of an operation permits statistical evaluation and determination of the average work center efficiencyoverall. Modifications to the standard load for an operation may result.

Quality control checks every produced or purchased product according to a more or less explicit or detailed quality control sheet.
A quality control sheet is a routing sheet that holds the process for quality assurance. 

With production orders, quality control can take place after each operation. Ideally, the person performing the operation should carry out quality control. However, quality control can also take place at the end of production. It may also serve to estimate process capability.[note 1510] For purchase orders, the receiving department inventories incoming receipts as to identity and quantity before transferring them to the quality control unit.

The production resources used for quality control are called quality control materials. The produced lot is designated “finished” or “received,” but also “in quality control”. The availability date is, e.g., the received date plus the lead time for completion of the quality control sheet. During execution of the control operations, errors are recorded.

An anticipated delay report is a report to materials management, regarding production or purchase orders that will not be completed on time.

Besides the new date, the anticipated delay report has to explain why the order is delayed.

The order termination report is the message that an order was completed. It contains the results and states that all resources used were recorded.

For logistics purposes, the final stage of the quality check judges the portions of the procured order lot as accepted or as rejected as scrap. The scrap (that is, the material outside of specifications) goes back to production for rework (that is, reprocessing to salvage the defective items, if this seems practical), or back to the supplier for replacement (or reduction of the total of the receipts).[note 1511] The yield (or the “good” quantity, that is, the acceptable material) moves to its destination: to stock, to a production process, or to sales.

Order termination is reported only when all resources used for a production order have been recorded, and when the accounting check for a purchase order has been performed. The latter is the comparison between the usable quantity of a shipment received and the corresponding purchase order position quantity.

15.3.4 Automatic and Rough-Cut Data Collection

Manual shop floor data collection, which uses operation cards, parts requisitions or picking lists, is slow, particularly for short operation times. Prompt recording of transactions requires additional administrative person­nel in the job shops. In addition, there is a great danger of erroneous data entries. For these reasons, one tries to record shop floor data automatically.

Automatic identification and data capture (AIDC) is a set of technologies that collect data about objects and send these data to a computer without human intervention. Examples are:

Bar codes: Information is coded in a combination of thick and thin lines. A light-sensitive pen reads and transfers this information to a computer.

Radio Frequency Identification (RFID) is an automatic identification technique, relying on storing and remotely retrieving data using RFID tags as transponders. A transponder is an electronic transmitter. An RFID tag can be attached to or incorporated into an object product, animal, or person for the purpose of identification using radio waves. Electronic product codes (EPCs) are used with RFID tags to carry information on the product to support warranty programs. 

Badges: A badge is generally a card with a magnetic strip. The strip contains information that can be read with a device and sent to a computer. 

The solutions developed thus far focus on the following techniques:

  • The use of bar codes or RFID to identify the operation or the allo­cation directly on the shop order routing or picking list. The use of operation and parts requisition cards is reserved for unplanned issuances or operations. The human operator is identified by means of his or her badge. This is usually the same magnetic card used for measuring the employee’s work hours.
  • A clock in the data processing system runs together with the trans­action and determines the actual time used through automatic re­cording of the start time and end time for the operation. The dif­ference between start time and end time yields time used, or the actual load. However, an unplanned issued quantity must still be recorded by hand. With this, a small source of error remains. In contrast to the grocery trade, for example, issuances in industrial production are not in units; under certain circumstances a large set of units may be issued instead.
  • Linking the data collection system to sensors that automatically count the goods produced or taken from stock. Such systems can be valuable for any kind of line production as well as for CNC or robot-supported production.
Rough-cut data collection takes into account the fact that the results of the entire operation are more important than the success of a single order.

The costs of data collection must stand in healthy relation to the benefits of data collection itself — namely, better control of the production and the procurement process. This condition is difficult to meet for all extremely short operations where the administrative time needed to record the operation is in the same range as the operation time itself:

  • Collective data collection for entire groups of short operations is possible. However, this requires the recording of the operations represented by this group or by collective data collection, so that the time recorded can ultimately be distributed among the individual operations according to a key. Since we often cannot determine this grouping in advance, it must be recorded at some point during the process. This quickly results in a quantitative data collection problem.

For group work, the recording of the actual processing time is often possible only for rough-cut operations, that is, for a combination of individual operations. This can only deal with all participating persons together and includes inter­operation times as well.

  • This combination may correspond to a rough-cut operation, which is sufficient for long- or medium-term planning. It may, however, be even rougher and cover operations for multiple orders, as was shown above for short operations. In all these cases, accounting for individual orders is questionable. Instead, accounting for the entire group over one time period replaces this; the presence times of the group members and the actual times for the rough-cut jobs deliv­ered are placed in relation to the corresponding standard times. This is also precise enough for payroll purposes (compensation); moreover, “success” is measured not only in terms of actual processing times, but also includes inter­operation times.
  • For the detailed operation, it is not possible in this way to compare the standard load to the actual load. In the case of well-tuned production — or procurement — with frequent order repetition this is actually not necessary, not even for cost estimating. The measure of success becomes the efficiency rate of the entire group (which is all the standard load divided by all the actual load; see Section 1.2.4), and not the costing of single jobs.

For machine-oriented work centers, especially for NC, CNC, and flexible manufacturing systems (FMS), as well as for automated stock transport systems, the solution for the future lies in inexpensive sensors and in the link to the computer that performs shop floor control.

For manual work centers, it is important that the workers do not need to leave their posts for data entry purposes and that they do not need to enter their identification anywhere. The company can introduce inexpensive data collection units that make use of bar code readers or transponders. These data collection units should be located right at the workstation and linked to an intranet. The employee badge identifies the individual employee.

There is an observation with all the techniques used for measuring job shop processes: Collection of excessively detailed data can influence processes to such an extent that without measurement the outcome as a whole would be different. This type of measurement falsifies the process (by slowing it down, for example) and should not be implemented.

Course sections and their intended learning outcomes

  • Course 15 – Order Release and Control

    Intended learning outcomes: Differentiate various techniques for order release. Explain in detail shop floor control. Present methods and techniques used for order monitoring and shop floor data collection. Describe distribution control.

  • 15.1 Order Release

    Intended learning outcomes: Describe order proposals for production and procurement as well as order release. Explain load-oriented order release (Loor) and capacity-oriented materials management (Corma).

  • 15.2 Shop Floor Control

    Intended learning outcomes: Describe the issuance of accompanying documents for production. Explain operations scheduling, dispatching, and finite forward scheduling. Present sequencing methods.

  • 15.3 Order Monitoring and Shop Floor Data Collection

    Intended learning outcomes: Describe recording issues of goods from stock and completed operations. Produce an overview on progress checking, quality control, report of order termination, and automatic and rough-cut data collection.

  • 15.4 Distribution Control

    Intended learning outcomes: Explain order picking, packaging, load building, and transportation to receiver.

  • 15.5 Summary


  • 15.6 Keywords


  • 15.7 Scenarios and Exercises

    Intended learning outcomes: Calculate examples for load-oriented order release (Loor) and for finite forward scheduling. Assess characteristics of capacity-oriented materials management (Corma) and of order Picking.

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