Posts Tagged ‘MRO’

Life Cycle Data Management Strategy

Thursday, September 3rd, 2009

Life Cycle Management implies a single “cradle to grave” plan that integrates production support planning, acquisition and sustainment strategies. Think about the importance of data flow and the criticality of accurate data throughout the complete life cycle of a piece of equipment: design, build, install, spare part acquisition, inventory management, maintenance, spare parts sharing and finally, asset disposal. From a data perspective, remember the old computer motto: “Garbage In, Garbage Out”.

What is your Life Cycle Data Management Strategy?

1) Drawing Libraries – The items in the library need to be cleansed and profiled to a classification schema. The schema requires standard naming conventions and technical descriptions. The schema can be designed within your company, priority purchased from another vendor or you can opt for using an open classification dictionary for public use such as the ECCMA eOTD.

2) Common Component Listing – provides a listing of preferred components that support the inventory management strategies for your organization. All equipment designers and builder are required to use the common components identified. Note: common components are set up in the drawing libraries.

3) Spare Part Acquisition – Place the components on purchasing contacts at the beginning of design, this will facilitate the ease of spare parts planning and purchasing. An item on contract provides purchasing the data needed to run analytical algorithms in order to better negotiate pricing organization wide. If the item is set up accurately to a standardized classification dictionary with technical descriptions only one time the whole organization can realize the benefits of the Life Cycle Data Management Strategy.

4) Inventory – supports optimal inventory management by promoting the ability to plan stocking levels and strategies with nearby facilities. Think about the implementation of spare parts sharing or an internal purchase first program. The most important requirement is the standardization or normalization of the data; the part needs to be classified only one-way and should be shown in every system the same way.

5) Maintenance –The use of standardized components coupled with a data management strategy allows the organization to streamline the number of different components used to serve the same function on different equipment. Also reducing the number of parts in inventory and maintenance management tasks.

Life Cycle Data Management Plans starts with component standardization and cleansing the data in your equipment drawing libraries and all downward systems including maintenance. This strategy avoids duplicate inventory items and at the same time promotes an internal purchase philosophy that puts a priority on inventory sharing before issuing supplier purchase orders. Standardizing inventory with information elements such as predefined stocking levels, identification of critical inventory, functionally equivalent item identification and purchasing analytics as well as enhanced vendor management are all necessary steps for a manufacturing business to remain competitive in today’s world of lean low overhead manufacturing.

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DATAForge LLC scheduled to present Maximo best practices at Purdue University

Wednesday, July 29th, 2009

DATAForge LLC is scheduled to present our best practice “Electronic Structured Spare Parts Data Population of Maximo” at the Facilities Management Maximo Users Group (FMMUG) http://www.fmmug.org/ hosted by Purdue University on October 11th and 12th. Setting up spare parts and tasking in Maximo starts at the beginning of equipment design with the bill of materials parts list, the equipment asset number and plant location. Our best practice, provides a complete and automatic electronic transfer of the Bill of Material for a piece of equipment that mashes up to an equipment listing with location. The data is imported with the item records referenced to a category key of perishable spare / non spare. The perishable spares are imported to a data verification tool where analysts process and cleanse the spare part records. Once the equipment with plant location and all associated spare parts are complete we use a simple to use interface for transfer of data to Maximo, thus giving users the power to move thousands of records at a time creating Equipment, Items, Companies, Spare Parts, etc. with all of the correct fields related, to take advantage of the Maximo hyper-linking ability. The results are a fully accurate data enabled Maximo without manual part verification or data entry of equipment, items, spare parts or companies. The documented time savings for one program is two skilled trade persons for two years. Look for our best practice case study in October.

DATAForgeTM LLC Managing the Automotive Industry Content Standardization Council (AICSC) Through ECCMA

Tuesday, July 21st, 2009

SOLON, OH–(Marketwire – July 21, 2009) – The ECCMA (Electronic Commerce Code Management Association) awarded DATAForge LLC the distinct honor of managing the Automotive Industry Content Standardization Council (AICSC).  Read More…

 

 

What is the Cost of Bad Data?

Friday, July 10th, 2009

How does a company apply a “cost” to bad data when the costs are so fragmented across the organization? There are obvious costs such as a part not being in inventory, purchasing has tried to buy the part but the supplier didn’t recognize the part number, now production is down and everyone is scrambling to find the replacement part. In this case the cost of the bad data can be assigned.

What about the other costs? What does it cost a global manufacturer the lack of visibility of the “spend” or the inability to manage vendors selling like or equivalent products?

It’s estimated that process failures and bad information cost $1.5 trillion or more in the U.S. alone.[i]


[i] Larry English, “Information Quality Tipping Point: Plain English about Information Quality,” DM Review, July 2007.

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Data Integrity – How is this really achieved?

Thursday, May 21st, 2009

Data integrity is the assurance that data is consistent and correct. Spare parts, sounds fairly simple?
What are the basic elements of a part record; name, part number, description? Data Integrity is used way too much but is a very vague concept. Let’s just look at the purchasing department; it is easy if the part records are only used by the purchasing department where the main objective is to purchase the item. This example is all the data that the buyer will need to purchase this switch.

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How would a buyer know that these are the same parts? Two different manufacturer names and two different part numbers; this scenario will cause duplication in a purchasing system. The result is the additional work of creating and maintaining two contracts but also cause downstream effects such as excess inventory with more than 1 stocking location, lack of a volume purchase or a global view.

 Question: Is the answer to always to confirm the actual manufacturer and set up supplier references?

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