Denton Engineering

with an average of over 10 years, we have gained outstanding experience delivering quality service to a wide range of discerning clients, gathering a considerable knowledge base working on projects, with a solid team of engineers and technicians

QUALITY ASSURANCE AND QUALITY CONTROL

An important goal of DENTON good practice guidance is to support the Industry standard of inventories and services that can be readily assessed in terms of quality and completeness. It is good practice to implement quality assurance and quality control (QA/QC) procedures in product and service delivery to accomplish this goal.

This guidance establishes good practice consistent with the Revised 2013 DENTON Guidelines for Industry Standard (DENTON Guidelines). The QA/QC good practice guidance outlined here reflects practicality, acceptability, cost-effectiveness, existing experience, and the potential for application on a worldwide basis. A QA/QC programme contributes to the objectives of good practice guidance, namely to improve transparency, consistency, comparability, completeness, and confidence in DENTON products and services.

The outcomes of the QA/QC process may result in a reassessment of inventory or source category uncertainty estimates. For example, if data quality is found to be lower than previously thought and this situation cannot be rectified in the timeframe of the current inventory, the uncertainty estimates would have to be re-evaluated. The terms ‘quality control’ and ‘quality assurance’ are often used incorrectly. Below definitions of QC and QA will be used for the purposes of DENTON good practice guidance.

DEFINITION OF QA/QC

Quality Control (QC) is a system of routine technical activities, to measure and control the quality of products and services as it is being developed. The QC system is designed to:

(i) Provide routine and consistent checks to ensure data integrity, correctness, and completeness;
(ii) Identify and address errors and omissions;
(iii) Document and archive inventory material and record all QC activities.

QC activities include general methods such as accuracy checks on data acquisition and calculations and the use of approved standardized procedures, measurements, estimating uncertainties, archiving information and reporting. Higher QC activities include technical reviews of source categories, activity and product factor data, and methods.
Quality Assurance (QA) activities include a planned system of review procedures conducted by personnel not directly involved in the inventory compilation/development process. Reviews, preferably by independent third parties, should be performed upon a finalized inventory following the implementation of QC procedures. Reviews verify that data quality objectives were met, ensure that the inventory represents the best possible estimates of products and services given the current state of scientific knowledge and data available, and support the effectiveness of the QC programme.

Before implementing QA/QC activities, it is necessary to determine which techniques should be used, and where and when they will be applied. There are technical and practical considerations in making these decisions. The technical considerations related to the various QA/QC techniques are discussed in general, and specific applications to services are described in the source category-specific good practice guidance. The practical considerations involve assessing Industry circumstances such as available resources and expertise and the particular characteristics. The level of QA/QC activities should be compatible with the methods for particular source categories.

quality control procedures

QUALITY CONTROL	PROCEDURE
Check that assumptions and criteria for the selection of activity are documented.	• Cross-check descriptions of activity with information on source categories and ensure that these are properly recorded and archived.
Check for transcription errors in data input and reference	• Confirm that bibliographical data references are properly cited in the internal documentation. • Cross-check a sample of input data from each source category (either measurements or parameters used in calculations) for transcription errors.
Check that data and information are calculated correctly.	• Reproduce a representative sample of data calculations. • Selectively mimic complex model calculations with abbreviated calculations to judge relative accuracy.
Check that parameter units are correctly recorded and that appropriate conversion factors are used.	• Check that units are properly labeled in calculation sheets. • Check that units are correctly carried through from beginning to end of calculations. • Check that conversion factors are correct. • Check that temporal and spatial adjustment factors are used correctly.
Check the integrity of database files.	• Confirm that the appropriate data processing steps are correctly represented in the database. • Confirm that data relationships are correctly represented in the database. • Ensure that data fields are properly labeled and have the correct design specifications. • Ensure that adequate documentation of database and model structure and operation are archived.
Check for consistency in data between source categories.	• Identify parameters (e.g. activity data, constants) that are common to multiple source categories and confirm that there is consistency in the values used for these services in facility management.
Check that the movement of inventory data among processing steps is correct.	• Check that data are correctly aggregated from lower reporting levels to higher reporting levels when preparing summaries. • Check that data are correctly transcribed between different intermediate products.
Check that uncertainties in services are estimated or calculated correctly.	• Check that qualifications of individuals providing expert judgment for uncertainty estimates are appropriate. • Check that qualifications, assumptions and expert judgments are recorded. Check that calculated uncertainties are complete and calculated correctly. • If necessary, duplicate error calculations or a small sample of the probability distributions used by Monte Carlo analyses.
Undertake review of internal documentation.	• Check that there is detailed internal documentation to support the estimates and enable duplication of the uncertainty estimates. • Check that inventory data, supporting data, and inventory records are archived and stored to facilitate detailed review. • Check integrity of any data archiving arrangements of outside organizations involved in inventory preparation.
Check methodological and data changes resulting in recalculations.	• Check for temporal consistency in time series input data for each source category. • Check for consistency in the algorithm/method used for calculations throughout the time series.
Undertake completeness checks.	• Confirm that estimates are reported for all source categories and for all years from the appropriate base year to the period of the current inventory. • Check that known data gaps that result in incomplete source category estimates are documented.
Compare estimates to previous estimates.	• For each source category, current standard services and inventory estimates should be compared to previous estimates. If there are significant changes or departures from expected trends, recheck estimates and explain any difference.

quality assurance procedures

QA PROCEDURES
DENTON Good practice for QA procedures requires an objective review to assess the quality of the products and services, and also to identify areas where improvements could be made. The process may be reviewed as a whole or in parts. QA procedures are utilized in addition to the QC. The objective in QA implementation is to involve reviewers that can conduct an unbiased review of the process. It is good practice to use QA reviewers that have not been involved in preparing the process. Preferably these reviewers would be independent experts from other company or an expert or group not closely connected with DENTON procedure compilation. Where third party reviewers outside the business are not available, staff from another operation part of DENTON not involved in the portion of the process being reviewed can also fulfill QA roles.
DENTON conducts a basic expert peer review prior to inventory submission in order to identify potential problems and make corrections where possible. It is also good practice to apply this review to all source categories in service delivery. However, this will not always be practical due to timing and resource constraints. Key source categories are given priority as well as source categories where significant changes in methods have been made.

EXPERT PEER REVIEW
Expert peer review consists of a review of calculations or assumptions by experts in relevant technical fields. This procedure is generally accomplished by reviewing the documentation associated with the process methods and results, but usually does not include rigorous certification of data or references such as might be undertaken in an audit. The objective of the expert peer review is to ensure that the results, assumptions, and methods are reasonable as judged by those knowledgeable in the specific field. Expert review processes may involve technical experts and, where a client has formal stakeholder and public review mechanisms in place, these reviews can supplement but not replace expert peer review.

REPORTING
DENTON report summary of implemented QA/QC activities and key findings as a supplement to best practice. However, it is not practical or necessary to report all the internal documentation that is retained by the DENTON. The summary should describe which activities were performed internally and what external reviews were conducted for each source category and on the entire system in accordance with the QA/QC plan. The key findings describe major issues regarding quality of input data, methods, processing, or archiving and show how they were addressed or plan to be addressed in the future.

DENTON ENGINEERING LIMITED, a company registered and incorporated with the Corporate Affairs Commission, is an Integrated Total Engineering Management Services Company and 21st century solution organization in Nigeria.

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Peterborough, PE7 8HU Cambridgeshire

+234(0)706 288 4189

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info@dentonlogistics.com

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