Posts Tagged ‘maintenance’

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Events DATAForge will be presenting at

Friday, September 11th, 2009

October 2009 is going to be a busy and exciting month for DATAForge. We are scheduled to present at two events and hope to see you all at both

DATAForge will be presenting at the FMMUG 2009 Best Practices to be held October 11th and 12th. This years event is to be hosted by Purdue University. The mission of the Facilities Management Maximo User Group (FMMUG) is to provide a forum for Maximo users in the facilities management industry to exchange information, methods and experiences. This exchange of information is designed to optimize the use of Maximo’s capabilities. For more information visit http://www.fmmug.org.

DATAForge will also be presenting on behalf of the Automotive Industry Content Standardization council at the 10th Annual ECCMA ISO 8000 Data Quality Conference on October 27th, 28th and 29th. This years event will be held at the historic Hotel Bethlehem in Bethlehem, Pennsylvania. Whether you are new to data quality or a seasoned professional, this conference will provide you with a unique opportunity to discuss the latest trends and check out the latest technology. If you have an interest in improving the accuracy of your vendor, material, service or asset masters, improving the descriptions in your ERP software or buy-side or sell-side catalogs or if you are looking for solutions to data integration challenges, the ECCMA conference is the place to be! Please visit the ECCMA website for more information.

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It’s Complicated

Wednesday, September 9th, 2009

At DATAForge we pride ourselves on designing simple, elegant, easy to use, web based software for a manufacturing demographic that has been flooded with overly complicated software, abound with options and restrictions, screens to control those options,restrictions and configurations. I’m tired of it. I don’t want you to get me wrong, there is certainly a time, place, and need for software that is configurable in every conceviable way. For example when a multi-state and international corporation is required by law to comply with one of the most complicated tax codes in the recorded history of Earth, then you get a pass for making an application complicated. In this case complication can and has saved many organizations millions or hundreds of millions of dollars, issues like The Sarbanes-Oxley Act of 2002 are not to be taken lightly.

The same logic of presenting every imaginable, option, configuration, button, screen, step, radio button, piece of information has been applied to many software packages. You would think in a large organization, simplicity would be king…not so…I am currently consulting with a large multi-national organization to help in the deploymentof a centralized system to house all product information for their MRO or Maintenance, Repair and Operations. Which, in practical terms, means that they are centralizing their databases of information required to order, maintain, and use any item that can potentially be purchased but does not go into their final product.

Not a small task by any measuring stick. Master Data Management, data cleansing, data normalization, intra-organization de-duplication are on the radar of most if not all large businesses. The most important part of the process is to choose application(s) that are the best fit for your organization, not the one that is made or owned by the largest company, and not the one who has the most clever marketing, not the one that appears in the latest report by the best marketed research firm (think about the ratings agencies who rated toxic subrime mortgage backed securities AA or AAA)

The software that was chosen xxxxxx (contractually obligated not to say the name) has one main screen for entering most of the data related to any given item, this screen contains no less than 50 possible fields in tabular form. There are also 3 additional screen each with less than 50 fields for data entry, these subsequent screens are used to associate ansillary information such as pictures to an item. The screens that DATAForge uses – one screen with 25 or less (depending on the type of data). The remainder of the information is gathered organically and seamlessly based on the way the application is used and who is using it.

When we design a solution the question on each team members mind is “How can I make this easier and faster to do for the end user?”

When evaluating an application force the vendor to show you how it will be used (not tell you), make them show you their solution is faster and more efficient. Lots of options, inputs, and fields are not always the users friend.

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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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Why Data Cleansing?

Thursday, August 27th, 2009

The statistics around data cleansing are overwhelming and there are mountains of discussions, white papers and tweets available pertaining to Data Quality, Data Profiling and Master Data Management. I think we need to take a step back and try to understand how and why data cleansing has become such a hot topic. You may have realized that business data typically isn’t as streamlined and efficiently maintained as we thought it was. Your organization may have shipped purchased items back because they were not what you thought you had ordered. In some cases another department was found to have the item in inventory, even though we have the item on urgent delivery status from a supplier because the item is set up under a different number or description, you couldn’t have possibly known the item was actually available from existing inventory.

The data quality issues that industries around the world are experiencing have occurred as a result of many years of manual inventory and purchasing record maintenance, through mergers and acquisitions of companies and business units as well as data migrations from various legacy systems into new fangled ERP black holes. There are a number of reasons why.

A common data trap frequently fallen into is assuming that just because you are implementing a new ERP system your organization will now have quality data. Remember the old computer motto – “Garbage In, Garbage Out”. Let me tell you based on first hand experience that there is nothing “sexy” about bad data when the production line is down or any other time.

Data Cleansing and Data Profiling is a very tedious and detailed oriented service. There are a number of key rules to follow whether the profiling and cleansing work is done internally or outsourced to someone who specializes in data cleansing. Here are some rules to consider before a project is started:

1) Conduct a detailed and comprehensive data mapping through all internal systems including engineering, purchasing, asset management, plant inventory management, etc. The goal is to standardize and document all data sources within the enterprise one time and ensure that each department is accounted for and determines what data elements are required to complete their business required tasks.

2) Build a central data cleansing database and make sure all locations using each item are referenced. This ensures that updated information will be passed back to the various legacy systems. You will need old information and updated information for this stage of the process.

3) The data cleansing database should include a balance of electronic scripting for data corrections and manual auditing. A solid process for answering questions needs to be set up. My preference is that the system should use a web utility that tracks data change history and other data related information such as contact information, issue resolution status, classification, questions and answers, etc.

4) The data needs to be referenced to a classification schema and a standard implemented for descriptions and properties. 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.

5) Free text is not our friend in the data standardization world. If all possible use a system that has built in data rules and ensure anyone entering data into the system understands the standards and the importance of quality data in addition to the high cost to businesses using bad data.

6) Data Cleansing and Profiling the proper way is not “cheap”, but the cost of cleaning the bad data is always less than the expenditures incurred by cleansing your data multiple times or continuing to operate your organization based on erroneous information generated from one or multiple dirty databases.

Cleansed data permits the removal of duplicated inventory items, an internal purchase philosophy that puts a priority on inventory sharing before issuing supplier purchase orders, standardizing inventory with predefined stocking levels, identifying critical pieces of inventory, identifying functionally equivalent items, use of engineering component standardization libraries and facilitates purchasing analytics as well as enhanced vendor management.

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The Spare Parts World and What It Could Be

Thursday, August 20th, 2009

The conundrum of spare parts management at a high level is perceived and often approached as a process that should be simple. Looking at it from the perspective of the many different entities that form the supply chain and are required to work together symbiotically—component manufacturers, Tier One and Tier Two suppliers, and OEM manufacturers—the logistical expertise needed to coordinate the information flow is anything but simple.

To realize cost savings from new process efficiencies, these separate legal entities need to integrate the information flow and internal groups within each entity such as purchasing, manufacturing engineering, plant maintenance, facilities management, warehousing, commodity management, and asset recovery. Each area must share the mission-critical master data related to the spare parts. Truly integrating the information flow within the conceivably 50-plus business units that indirectly work together across the automotive supply chain to deliver just one item to an OEM sounds literally impossible and cost prohibitive. However, your opinion may change when you read the next couple sentences.

It is estimated that process failures and bad information cost business $1.5 trillion or more in the U.S. alone (Larry English, 2007). A study of large companies, a majority of which have revenues of more than $1 billion, found that 31 percent believe that their costs for incorrect data are $1 million or more per year (Dave Waddington, 2008). The most common element needed by (and from) all involved in the supply chain of the spare parts that keep our lines running is data quality and content as information is transmitted from one organization to another.

Figure 1. Typical Supply Chain Spare Part Data and Information Flow

There is a lot of activity and even more information available around Master Data Management (MDM). MDM and data quality initiatives have become an industry trend these days. To champion a successful MDM effort, formal strategies regarding data standardization in content and structure, as well as import, storage, display, and transmission from your enterprise resource planning (ERP) systems to industry partners are mandatory.

Every supplier, OEM, and manufacturer is using a unique set of data standards to attempt to achieve true “quality” for their data. But how powerful, efficient and beneficial to the automotive industry can the use of silo developed standards be? If all partners were using the same data standards, naming conventions, and requirements to describe spare parts, we can greatly streamline the process needed to exchange the information and at the same time reduce the number of physical and business process failures resulting from the low-quality descriptions contained in our legacy systems, and in most cases, new state of the art ERP systems.

The elements required to achieve a symbiotic information flow for the automotive industry are the same:

A common understanding of what data is needed for a particular class or type of item;
A common method to store the data;
A common method to display the data; and
A common method to transmit the data to those entities that do business together.
The answer is to simplify and standardize the methods used for the exchange of structured, accurate, and efficient data-sharing in an automated fashion, rather than manually sharing as it has traditionally been done. The Electronic Commerce Code Management Association (ECCMA) and DATAForge LLC have formed the Automotive Industry Content Standardization Council (AICSC). The purpose of the council is to facilitate the addition of automotive industry specific terminology to the electronic Open Technical Dictionary (eOTD), create identification guides for quality descriptions, or data requirement statements for individuals, organizations, locations, goods and services.

This also helps develop an automotive supply chain specific spend analysis classification. The dictionary being maintained by ECCMA and the AICSC is ISO standard and public domain; any organization can benefit from its use. ECCMA and the AICSC work with automotive-centric businesses to standardize the way data and information is stored, viewed, and exchanged.

Figure 2. Quality Description:

ECCMA has brought together thousands of experts from around the world and provides them a means of working together in the fair, open, and extremely fast environment of the Internet to build and maintain the global, open-standard dictionaries that are used to unambiguously label information. ISO 22745 spare parts data is capable of being used in any ISO 8000 computer application (neutral exchange), is easily translated, and must stand the test of time (long-term data retention) by using a public domain concept identifier.

Jacqueline Roberts is vice president of DATAForge LLC. For more information about ECCMA, visit the ECCMA Web site.

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ISO 22745 Standard Based Exchange of Product Data

Thursday, August 20th, 2009

When a spare parts list, bill of material, or other product information for your ERP or inventory system is received, what processes do you follow to make sure the data is accurate and complete?

Typically, maintenance or inventory information is not given any due diligence until it is needed. For instance, a bill of material (BOM) is received, all the parts are set up in your ERP system, and the item record sits untouched until you need to place an order or set the item up in your maintenance system. Then you find that the part number is inaccurate and the supplier doesn’t recognize it, or there is an essential piece of information missing from the description needed to complete the order and bring the line back up. There is a solution: ISO-22745.

The ISO-22745 standard provides the framework needed for any organization to conduct business with internationally recognized data quality. Its most basic purpose is to provide a means to realize the benefits of ISO-8000, which is the ability to specify syntax, semantic encoding, and specification of data requirements for messages containing master data that is exchanged between organizations in the supply chain. Once an organization begins to standardize the descriptions it uses to describe materials, the organization can also begin to see cost savings and cost avoidance by implementing business intelligence algorithms to identify conditions such as duplicate items in inventory, purchase price disparities between facilities, vendor reductions, and identification of functional equivalent items.

ISO-22745’s primary facilitator is the open technical dictionary (OTD), a database of concept IDs and associated descriptive words used to “tag” individual data elements. Once each element is tagged with the concept ID from the OTD, the descriptive elements can be stored, sent, received, and displayed by different organizations without losing any meaning. This is done for multiple languages at once, with no need to translate into multiple languages independently.

ISO-22745 also includes guidelines for the use of identification guides (IG). An identification guide is a statement of requirements describing what data is needed about an item. If all elements are included in the description, this IG facilitates the machine-aided analysis of data quality because we have a clear understanding of what data is required without a person having to review the data.

ISO-22745 describes XML formats that can be used to automate the exchange of ISO-8000 master data.

i-xml is used to specify the data requirements or IG.
q-xml is used to query another organization for the data elements specified in the IG.
r-xml is used to reply to requests for specific data elements.
Together, these formats allow for the machine aided exchange of master data.

The Electronic Commerce Code Management Association (ECCMA) provides a very mature OTD, known as eOTD, which contains more than 440,000 terms that can be used to generate descriptions. ECCMA and DATAForge have also formed the Automotive Industry Content Standardization Council (AICSC). The AICSC is here to help organizations move from proprietary methods of managing descriptions to an ISO method that includes working together as an industry to meet the common goal of lowering operating overhead related to catalog maintenance.

Chris Roberts is an associate product manager at DATAForge™ LLC

For more information on AIAG’s activities and initiatives in electronic commerce, visit the AIAG Web Site or contact Mohammad Abidi.

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The Spare Parts World

Tuesday, August 11th, 2009

Spare parts management at a high level is perceived and often approached as a process that should be simple. Looking at it from perspectives of the many different entities that form the supply chain and are required to work together – component manufacturers, tier 1 suppliers, tier 2 suppliers, and manufacturers, the logistical expertise needed to coordinate the information flow is anything but simple.

To realize cost saving from new process efficiencies, these separate legal entities need to “integrate” the information flow to manufacturers and within each manufacturer to internal groups such as purchasing, manufacturing engineering, plant maintenance, facilities management, warehousing, commodity management, and asset sharing / recovery need to share the mission critical master data related to the spare parts. A truly integrated information flow could conceivably touch a number of business units that indirectly work together across the supply chain to deliver just one item to a manufacturer. The most common element needed by (and from) all involved in the supply chain of the spare parts that keeps the equipment running is data standardization, data quality and an electronic method of transmittal. A study of large companies, a majority of which have revenues of more than $1 billion, found that 31% believe that their costs for incorrect data are $1 million or more per year.1

Data standardization and data cleansing cost should be covered with cost saving initiatives. In addition to the initial data cleanup; strong data governance processes should be implemented for on-going data setups.

1Dave Waddington, “Growing Adoption of Master Data Management by Business?” citing an Information Difference survey of 112 companies, 65% of which had revenues of more than $1 billion, IT-Director.com, IT Analysis Communications Ltd., June 23, 2008.

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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.

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Achieving buyer/supplier information synergy… eOTD, XML, People

Thursday, June 11th, 2009

What comes to mind when you read those words? Does your organization have issues attaining the product data you need to run your manufacturing operations?

Buyer/supplier information synergy to me means that at any given time, if a piece of data is needed to complete a product description or a piece of data is needed to place a product or service order that is not available in your ERP applications, your suppliers are willing and able to provide the piece of data automatically without human intervention.

That probably sounds ridiculous.

This situation probably sounds more familiar:

1.) New equipment is installed
2.) The recommended spares list is loaded directly into ERP
3.) The new equipment malfunctions, goes down
4.) Production stops
5.) The maintenance department attempts to replace failed component only to find there is no inventory
6.) Maintenance frantically calling machine builder/suppliers/plant engineering to identify the failed component

This may be an over simplification or might not be something your organization can relate to, but, there are several types of technology and business process that enable prevention of this scenario and other problems that plague the large manufacturers supply chain.
—a common unified schema or dictionary used by all commercial organizations to label product information (eOTD)
—a common method of transmitting this information directly into ERP prior to the need arising to replace a component (xml)
—develop a supporting business process to ensure the needed information is requested (people)

As manufacturers/suppliers/BPO providers we all need to work together to move to a common method of requesting, transmitting and receiving the information we need to keep our operations running.

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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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