Relevant bibliographies by topics / Supplier data quality

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Supplier data quality'

Author: Grafiati
Published: 4 June 2021
Last updated: 16 February 2022

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Journal articles on the topic "Supplier data quality"

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Cleff, Thomas. "Using International Trade Data for Evaluating the Product Specific Competitiveness and Supplied Product Quality of Countries: A Successful Example of Applied Theory." Gadjah Mada International Journal of Business 8, no. 2 (June 12, 2006): 229. http://dx.doi.org/10.22146/gamaijb.5621.

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This paper proposes a simple regression-based method for reducing the complexity of decisions in the international procurement process. Based on foreign trade data, the method uses indicators, which allow a product specific cross-section and longitudinal-section valuation of the international competitiveness and the supplied product quality of all potential supplier countries. The method thus provides a variety of information for procurement departments, including the present level and the dynamic of competitiveness and product quality for the potential supplier countries within every product group of the international product nomenclature (Combined System and the Harmonised System). Potential supplier countries --the companies of which have proven to be particularly competitive in the different product quality stages-- are identified. This pre-selection of countries enables the companies to limit their search for potential suppliers to the selected supplier countries. High search costs are subsequently reduced and trend prognoses can be constructed.
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POLANSKY, ALAN M. "SUPPLIER SELECTION BASED ON BOOTSTRAP CONFIDENCE REGIONS OF PROCESS CAPABILITY INDICES." International Journal of Reliability, Quality and Safety Engineering 10, no. 01 (March 2003): 1–14. http://dx.doi.org/10.1142/s0218539303000968.

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The supplier selection problem consists of selecting the best of several possible suppliers for a product. The selection criteria, in the absence of considerations such as cost, are based on a quality metric such as the capability of the supplier's manufacturing process. Because quality metrics are estimated based on sample process data, the inherent variability in the estimates must be accounted for when selecting the best supplier. In this paper we consider a methodology based on the bootstrap that assigns confidence levels to each of the suppliers. These confidence levels are designed to reflect the amount of confidence we have that the supplier actually has the best quality metric, conditional on the observed samples. The methodology is demonstrated using two examples.
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Chen, Kuen-Suan, Tsang-Chuan Chang, and Chien-Che Huang. "Supplier Selection by Fuzzy Assessment and Testing for Process Quality under Consideration with Data Imprecision." Mathematics 8, no. 9 (August 24, 2020): 1420. http://dx.doi.org/10.3390/math8091420.

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Supply chain management models integrate upstream and downstream organizations to enable rapid response to consumer needs. For the manufacturing industry, the process quality of suppliers is thus the foundation of sustainable growth for firms and an important indicator of whether a firm can effectively reduce waste and protect the environment. To this end, this paper proposes a model of supplier selection for manufacturers based on process quality assessment. First of all, Six Sigma quality index Qpk is adopted as the assessment tool to conveniently measure the quality level of process. Practical applications require estimates of Qpk from the data collected to analyze the process quality of each supplier. The fact that uncertainty is unavoidable in the collected data means that using the crisp estimate of Qpk can lead to misjudgment of the process quality. To enhance the reliability of evaluation and reduce the risk of misjudgment, the fuzzy number Q^˜pk is proposed to perform the fuzzy testing of two indices Qpk provided by suppliers with the intent of making reliable decisions on supplier selection.
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Adi Wicaksono, Purnawan, I. Nyoman Pujawan, Erwin Widodo, Sutrisno, and Laila Izzatunnisa. "Mixed integer linear programming model for dynamic supplier selection problem considering discounts." MATEC Web of Conferences 154 (2018): 01071. http://dx.doi.org/10.1051/matecconf/201815401071.

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Supplier selection is one of the most important elements in supply chain management. This function involves evaluation of many factors such as, material costs, transportation costs, quality, delays, supplier capacity, storage capacity and others. Each of these factors varies with time, therefore, supplier identified for one period is not necessarily be same for the next period to supply the same product. So, mixed integer linear programming (MILP) was developed to overcome the dynamic supplier selection problem (DSSP). In this paper, a mixed integer linear programming model is built to solve the lot-sizing problem with multiple suppliers, multiple periods, multiple products and quantity discounts. The buyer has to make a decision for some products which will be supplied by some suppliers for some periods cosidering by discount. To validate the MILP model with randomly generated data. The model is solved by Lingo 16.
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Hutagalung, Juniar. "Studi Kelayakan Pemilihan Supplier Perlengkapan Dan ATK Menggunakan Metode SAW (Simple Additive Weighting)." J-SAKTI (Jurnal Sains Komputer dan Informatika) 3, no. 2 (September 13, 2019): 356. http://dx.doi.org/10.30645/j-sakti.v3i2.154.

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Office Supplies and Stationery (ATK) are equipment that is often used in offices, companies and organizations, include cabinet filling, perforators, calculators, paper clips, staplers, numerators, guides, flashdisks, paper punches, pens and paper, paper shredder, computers, printers, facsimile machines, photocopiers, archive folders and cash registers, office furniture. Supplier is part of the supplier chain that influences the development of a company. Problems that are often experienced by PT. PLN Engineering such as late arrivals and lack of quality equipment and stationery from suppliers, therefore it needs to be re-ordered or returned to suppliers, so that time is wasted. Storage of data on procurement of equipment and stationery that are still conventional so that it is not effective and efficient in terms of time, cost and energy, let alone supplier selection which is still subjective. The purpose of this study makes it easier for competent parties to make decisions at PT. PLN Engineering in selecting the best supplier to be consistent in maintaining the determined criteria so as to minimize the risk and not disappoint the company. Incorrect supplier selection affects the quality and costs incurred in buying equipment and stationery from suppliers, how to overcome them requires a decision support system (SPK) that is able to accurately select the most suitable supplier. The method of Simple Additive Weighting (SAW) combined with fuzification is the right method for evaluating the best suppliers. The most important criteria are Price of Goods, Quality of Goods, Delivery Time, Location Distance, Goods Packaging, Accuracy of Goods, Flexibility, Track Record. The conclusion of the test results is the SAW method is able to show that the ranking of the best suppliers with the highest value of 0.89 is UD. Bintang Mulia.
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Djasmayena, Selvia, Yuhandri Yunus, and Rezi Elsa Putra. "Pemilihan Supplier Obat yang Tepat Menggunakan Metode Multi Attribut Utility Theory." Jurnal Informasi & Teknologi 1, no. 4 (December 31, 2019): 47–54. http://dx.doi.org/10.37034/jidt.v1i4.27.

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Drug suppliers are those who sell and distribute drugs to pharmacies or sections that carry out pharmaceutical activities. Selection of the right supplier can support the operational activities of the pharmacy. Pharmacists must know the right criteria in choosing a supplier. Criteria determined by pharmacies not all suppliers can fulfill it. Overcoming this decision support system is very necessary in the selection of suppliers. Multi-Attribute Utility Theory is a ranking method that helps in supporting supplier selection decisions at Pekanbaru Assyafni Pharmacy. Supplier selection uses 15 sample supplier data and 5 criterion data used as a basis for supplier selection. Such as drug production, delivery time, quality stability, service response, and guarantee. The results of the study get a high degree of accuracy that is 86.67% of the right suppliers and in accordance with the realization of test data. So this research is very important in choosing the right supplier.
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Hanum, Bethriza, Titia Izzati, and Andi Cakravastia. "Supplier Selection on Rendement Rate of Patchouli Leaf." International Journal of Engineering & Technology 7, no. 3.7 (July 4, 2018): 130. http://dx.doi.org/10.14419/ijet.v7i3.7.16254.

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The aim of research is to design the model of rendement rate by considering the criteria of patchouli leaf and designing a good supplier selection model to maximize the company profit by considering the acceptance of the patchouli oil rendement rate. The selection of suppliers discussed is to consider the quantity of goods offered by suppliers, demand, budget and acceptance limitation of rendement rate. To overcome these limitations, it is necessary to develop a supplier selection model that takes into consideration the quantity limitation of goods offered by the supplier and the acceptance of the rendement rate by using Linear Programming (LP) method. The result of the research shows that the determination model of the rendement rate developed to determine the percentage of Rendement Rate (RR) of each raw material supplied by the supplier so that the company can know the quality of patchouli leaf based on the type of patchouli leaf. The analysis result of numerical sample calculation shows that the selected supplier is not a supplier with good patchouli leaf criteria, the analysis result of parameter changes in oil demand and budget indicate that when oil demand is increased over the benchmark data, the model output is insensitive, but when demand is lowered below the benchmark data, the model output looks sensitive.
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Bao, Xi, and Fenfen Li. "A methodology for supplier selection under the curse of dimensionality problem based on fuzzy quality function deployment and interval data envelopment analysis." PLOS ONE 16, no. 7 (July 14, 2021): e0253917. http://dx.doi.org/10.1371/journal.pone.0253917.

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Supplier selection is an important decision-making problem, which involves many quantitative and qualitative factors incorporating vagueness and imprecision. This study proposes a novel fuzzy multi-criteria decision-making framework for supplier selection, which integrates quality function deployment (QFD) and interval data envelopment analysis (DEA). The proposed methodology allows for considering the relationships among the product features and supplier evaluation criteria (SEs) and the impacts of inner dependence among SEs by constructing a house of quality (HOQ). Considering that the number of supplier evaluation indicators is greater than the number of suppliers in some cases, the curse of dimensionality problem usually exists. To solve this problem, we combine the HOQ, interval DEA models, and forward-stepwise selection approach to screen supplier evaluation indicators and select the best supplier(s). Through the two-stage supplier selection method, we can achieve the double screening of indicators and determine the final supplier(s). Finally, the application of the proposed framework is demonstrated through a numerical example and a sensitivity analysis is also carried out to verify the stability of the proposed methodology. This study focuses on supplier selection based on the combination of fuzzy QFD and interval DEA, and also provide a new two-phase methodology for DEA indicator screening.
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Shu, Ming-Hung, and Hsien-Chung Wu. "Quality-based supplier selection and evaluation using fuzzy data." Computers & Industrial Engineering 57, no. 3 (October 2009): 1072–79. http://dx.doi.org/10.1016/j.cie.2009.04.012.

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Shabani-Naeeni, Fereshte, and R. Ghasemy Yaghin. "Incorporating data quality into a multi-product procurement planning under risk." Journal of Business & Industrial Marketing 36, no. 7 (January 14, 2021): 1176–90. http://dx.doi.org/10.1108/jbim-02-2020-0108.

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Purpose In the data-driven era, the quality of the data exchanged between suppliers and buyer can enhance the buyer’s ability to appropriately cope with the risks and uncertainties associated with raw material purchasing. This paper aims to address the issue of supplier selection and purchasing planning considering the quality of data by benefiting from suppliers’ synergistic effects. Design/methodology/approach An approach is proposed to measure data visibility’s total value using a multi-stage algorithm. A multi-objective mathematical optimization model is then developed to determine the optimal integrated purchasing plan in a multi-product setting under risk. The model contemplates three essential objective functions, i.e. maximizing total data quality and quantity level, minimizing purchasing risks and minimizing total costs. Findings With emerging competitive areas, in the presence of industry 4.0, internet of things and big data, high data quality can improve the process of supply chain decision-making. This paper supports the managers for the procurement planning of modern organizations under risk and thus provides an in-depth understanding for the enterprises having the readiness for industry 4.0 transformation. Originality/value Various data quality attributes are comprehensively subjected to deeper analysis. An applicable procedure is proposed to determine the total value of data quality and quantity required for supplier selection. Besides, a novel multi-objective optimization model is developed to determine the purchasing plan under risk.
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Dissertations / Theses on the topic "Supplier data quality"

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GORDOS, PYGMALION-ALEXANDROS, and JONAS BULOVAS. "The importance of supplier information quality in purchasing of transport services." Thesis, KTH, Industriell Marknadsföring och Entreprenörskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-236510.

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An important prerequisite for successful supply chain integration is the ability to convert data into information combined with structured storing and sharing processes. The purpose of this master thesis is to investigate potential relation between supplier data quality and performance of purchasing of transport services. The output of the thesis generates evidence about the imperative to emphasize on the supplier data quality throughout the supplier selection process. A supplier data quality assessment framework consisting of 4 dimensions - ease of manipulation, accessibility, accuracy and completeness, is developed as the core product of this research project. The weights of these dimensions were assigned specifically for the case company - Cramo, to determine the quality score for a selected sample of carriers. A coefficient k1 representing the ratio of transport expenditure over sales was introduced to facilitate the identification of relation between supplier data quality and transport expenditure. Business units served by transport companies with higher quality data displayed a lower k1, consequently, paying less for the transport services in comparison to their revenue than business units served by carriers with lower data quality score. The framework developed is adaptable - dimensions and metrics can be added or excluded according to situational factors and case peculiarities. The application of the supplier data quality assessment framework allows for a more objective and streamlined supplier selection. It stresses on the overall costs experienced during the period of cooperation. The finding regarding the importance of supplier data quality in purchasing of transport services can be nonetheless generalized for other cases when companies strive for achieving better informed strategic decisions.
En viktig förutsättning för framgångsrik integration av leverantörskedjor ligger i förmågan att omvandla data till information, kombinerat med en strukturerad lagrings- och delningsprocess. Syftet med denna masteruppsats är att undersöka potentiell relation mellan leverantörers datakvalitet och hur effektivt inköpet av transporttjänsterna är. Utfallet av uppsatsen understryker vikten av att beakta leverantörers datakvalitet i alla delar av en upphandling. Som produkt av denna uppsats har en utvärderingsmall för leverantörers datakvalitet utvecklats. Den består av fyra dimensioner – Hanterbarhet, tillgänglighet, noggrannhet samt fullständighet. De olika dimensionerna är viktade specifikt för det studerade företaget – Cramo, för att fastslå kvalitetsindex för ett urval av deras transportörer. En koefficient - k1- infördes för att representera förhållandet mellan transportkostnad och försäljning. Detta för att underlätta identifieringen av potentiell relation mellan datakvalitet och transportkostnad. Depåer vars transportörer kunde uppvisa en högre datakvalitet hade ett lägre koefficientvärde (k1). Alltså fanns ett samband mellan hög datakvalitet och lägre transportkostnad i förhållande till försäljning. Den utvecklade bedömningsmallen är anpassningsbar – dimensioner och mått kan enkelt adderas eller elimineras utifrån rådande omständigheter i varje fall. Bedömningsmallen ger möjlighet till en mer objektiv och harmoniserad leverantörsbedömning. Mallen understryker även vikten av att beakta den totala kostnaden under avtalstiden. Kunskapen från denna uppsats kring vikten av datakvalitet gällande just transportinköp kan även generaliseras till andra fall där företag strävar mot bättre informerade strategiska beslut.
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Loudon, Melissa. "Data management and reporting for drinking water quality monitoring in community-managed supplies." Master's thesis, University of Cape Town, 2007. http://hdl.handle.net/11427/5031.

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Includes bibliographical references (leaves 111-126).
Water Service Authorities, which may be district municipalities with hundreds of community-managed supplies under their jurisdiction, are legally responsible for ensuring the quality of water supplied to all consumers. Without the assistance of communities, this requirement, which would involve regular testing in many remote and inaccessible supplies, is extremely difficult to fulfil. Water Service Authorities also struggle to respond timeously to problems in remote supplies, as they are often unaware of the problem for some days. Two-way communication between the Water Service Authority and the Community-based Water Services Provider is therefore essential to an effective monitoring programme. Information and communication technologies, particularly mobile phones on the cellular network, offer potential solution to the challenge of supporting community-managed supplies. Following an investigation into the information needs of various stakeholders in community management, a prototype drinking water quality information system for community-managed supplies was developed.
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Smith, Tamara L. "Associations between Fecal Indicator Bacteria Prevalence and Demographic Data in Private Water Supplies in Virginia." Thesis, Virginia Tech, 2013. http://hdl.handle.net/10919/50985.

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Over 1.7 million Virginians rely on private water systems to supply household water. The heaviest reliance on these systems occurs in rural areas, which are often underserved in terms of financial resources and access to environmental health education. As the Safe Drinking Water Act (SDWA) does not regulate private water systems, it is the sole responsibility of the homeowner to maintain and monitor these systems.
    Previous limited studies indicate that microbial contamination of drinking water from private wells and springs is far from uncommon, ranging from 10% to 68%, depending on type of organism and geological region. With the exception of one thirty-year old government study on rural water supplies, there have been no documented investigations of links between private system water contamination and household demographic characteristics, making the design of effective public health interventions, very difficult.
    The goal of the present study is to identify potential associations between concentrations of fecal indicator bacteria (e.g. coliforms, E. coli) in 831 samples collected at the point-of-use in homes with private water supply systems and homeowner-provided demographic data (e.g. homeowner age, household income, education, water quality perception). Household income and the education of the perceived head of household were determined to have an association with bacteria concentrations. However, when a model was developed to evaluate strong associations between total coliform presence and potential predictors, no demographic parameters were deemed significant enough to be included in the final model. Of the 831 samples tested, 349 (42%) of samples tested positive for total coliform and 55 (6.6%) tested positive for E. coli contamination. Chemical and microbial source tracking efforts using fluorometry and qPCR suggested possible E. coli contamination from human septage in 21 cases.  The findings of this research can ultimately aid in determining effective strategies for public health intervention and gain a better understanding of interactions between demographic data and private system water quality.

Master of Science
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Chiang, Chin-Yi, and 蔣靜宜. "Supplier Selection and Evaluation Using Fuzzy Quality Data and Their Applications to Touch Screen." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/06153920813309096463.

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碩士
國立高雄應用科技大學
工業工程與管理系
97
The purchasing function directly affects the competitive ability of a firm. Since the determination of suitable suppliers from a set of suppliers has become a key strategic consideration, managers need to periodically evaluate suppliers on the basis of their products quality to select suppliers whose quality characteristics of products meet the standards. The fuzzy data commonly existing in our reality world, in this fuzzy environment, the quality-based supplier selection is proposed in this paper. The quantification of the process capability is effective to understand the quality of the units shipped from a supplier. For the purpose of constructing the membership function of fuzzy capability-index estimate for each supplier, we apply resolution identity theorem, a renowned result in fuzzy sets theory, in terms of solving optimization problems. The preferable suppliers are selected by using a ranking method of fuzzy preference relation of suppliers. Finally, a case study of touch screen is provided to describe the applicability incorporating the fuzzy data into the problem of quality-based supplier selection and evaluation. Keywords: Supplier selection; Fuzzy number; Resolution identity; Fuzzy preference relation; Optimization.
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Books on the topic "Supplier data quality"

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Robinson, Keith W. Availability and suitability of data from public water-supplier sources for use in water-quality assessments. Pembroke, N.H: U.S. Dept. of the Interior, U.S. Dept. of Interior, U.S. Geological Survey, 1998.

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FEDERAL AVIATION ADMINISTRATION. Quality assurance controls for product acceptance software. [Washington, D.C.] (800 Independence Ave., S.W., Washington 20591): U.S. Dept. of Transportation, Federal Aviation Administration, 1993.

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Galway, Lionel A. Data quality problems in Army logistics: Classification, examples, and solutions. Santa Monica, CA: Rand, 1996.

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Reyes, Betzaida. Occurrence and distribution of organic chemicals and nutrients and comparison of water-quality data from public drinking-water supplies in the Columbia Aquifer in Delaware, 2000-08. Reston, Va: U.S. Dept. of the Interior, U.S. Geological Survey, 2010.

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Software development and quality assurance for the healthcare manufacturing industries. Buffalo Grove, IL: Interpharm Press, 1994.

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Software development and quality assurance for the healthcare manufacturing industries. 2nd ed. Buffalo Grove, Ill: Interpharm Press, 1997.

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Frey, Michelle M. Practical application of online monitoring. Denver, CO: Awwa Research Foundation, 2004.

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Brdicko, Jan. True shape and defects data from MPB affected stems. Victoria, B.C: Pacific Forestry Centre, 2007.

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California. Bureau of State Audits. Department of Health Services: Despite shortcomings in the Department's monitoring efforts, limited data suggest its two-plan model does not adversely affect quality of and access to health care. Sacramento, Calif. (555 Capitol Mall, Suite 300, Sacramento, 95814): Bureau of State Audits, 1999.

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Office, General Accounting. Medicare: Federal efforts to enhance patient quality of care. Washington, D.C: The Office, 1996.

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Book chapters on the topic "Supplier data quality"

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Al Salem, Aqeel, Anjali Awasthi, and Chun Wang. "A Multicriteria Multistep Approach for Evaluating Supplier Quality in Large Data Sets." In Springer Series in Reliability Engineering, 3–25. London: Springer London, 2015. http://dx.doi.org/10.1007/978-1-4471-6778-5_1.

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Jana, Susovan, Bijan Sarkar, and Ranjan Parekh. "A Holistic Framework for Quality Evaluation of Fruits and Vegetables Suppliers." In Lecture Notes on Data Engineering and Communications Technologies, 155–68. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4968-1_13.

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Markowicz, Iwona, and Paweł Baran. "Identification of EU Countries Due to the Quality of Data on Intra-Community Supplies of Goods Shipped from Poland in the Years 2005–2017." In Experimental and Quantitative Methods in Contemporary Economics, 311–22. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30251-1_22.

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Adeleke, M. L., D. Al-Kenawy, A. M. Nasr-Allah, M. Dickson, and Desalegn Ayal. "Impacts of Environmental Change on Fish Production in Egypt and Nigeria: Technical Characteristics and Practice." In African Handbook of Climate Change Adaptation, 789–805. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-45106-6_153.

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AbstractA survey approach was applied to examine the technical characteristics of fish farming practice in Egypt and Nigeria. Critical issues such as floods and other vices were considered in bringing out the inference and level of aquaculture in both countries. Multistage sampling technique was used to select the study area and the number of respondents. Both primary and secondary data were used in the analysis. Eighty fish farmers were randomly selected from each of the country, making a total of 160 respondents. The socioeconomic characteristics revealed that aquaculture is an antique venture in Africa with Egypt taking the lead, i.e., 99% of the respondents practice in large-scales production of more than 11 Fadden/acre per, and 100% males depend mainly on agricultural drainage water for their earthen ponds. Ninety-eight percent cultured tilapia (Oreochromis niloticus) which was believed to have originated from the Nile River. In terms of financial performance and partial economic analysis, tilapia production commands more sales in Egypt, while catfish (Clarias) production is seen as a promising venture in Nigeria. The fish farmers have various perceptions and reactions toward environmental changes factors such as cost of labor/manpower and inputs, poor water quality, and fish extension services, and climate change impedes aquaculture development in the countries. To achieve the scale of aquaculture expansion as observed in Asian and other developed part of the world, efforts should be geared toward continental and regional integration in order to encourage aquaculture practices in Nigeria and other parts of Africa. More so, government intervention and incentives should be paramount in Egypt to reduce the excessive exploitation of the private input suppliers.
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Arani, Alireza Shayan, Hamed Nozari, and Meisam Jafari-Eskandari. "Performance Evaluation of Suppliers with Undesirable Outputs Using DEA." In Data Envelopment Analysis and Effective Performance Assessment, 312–27. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-0596-9.ch008.

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Performance evaluation and selection and ranking of suppliers is very important due to the competitiveness of companies in the present age. The nature of this kind of decision is usually complex and lacks clear structure and many qualitative and quantitative performance criteria such as quality, price, flexibility, and delivery times must be considered to determine the most suitable supplier. Given that in the supplier evaluation may offer undesirable outputs and random limitations, providing a model for evaluating the performance of suppliers is of utmost importance. With regard to the issue of multi-criteria selection of suppliers, one of the most efficient models to choose suppliers is DEA.in this paper to measure the strong performance and development of undesirable output and random limitations concept the SBM model is used.
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Saleh, Feras. "Multi-Tier Supplier Selection Using Total Cost of Ownership and Data Envelopment Analysis." In Handbook of Research on Interdisciplinary Approaches to Decision Making for Sustainable Supply Chains, 597–622. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-5225-9570-0.ch028.

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Quality management across multiple tiers is vital to minimize cost of quality in global supply chains. In this chapter, the authors address the problem of supplier selection in multi-tier global supply chains with the purpose of overall quality management. A hybrid approach based on total cost of ownership (TCO) and network data envelopment analysis (DEA) is proposed. The TCO looks beyond the quoted cost to cover additional true costs related to the entire purchasing cycle. The cost categories included are quoted price, manufacturing costs, quality costs, design costs, logistics costs, after sales service, and social/environmental costs. Network DEA is used to rank the suppliers based on the TCO cost categories. The advantage of network DEA is its ability to investigate intermediate linkages between different stages of the supply chain. The results of network DEA are efficient suppliers and improvement targets for inefficient suppliers for improving overall quality in global supply chains. A numerical application is provided.
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Otto, Boris. "Quality Management of Corporate Data Assets." In Quality Management for IT Services, 193–209. IGI Global, 2011. http://dx.doi.org/10.4018/978-1-61692-889-6.ch010.

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Corporate data assets such as customer, material, and supplier master data are critical when it comes to fulfilling business requirements such as compliance to regulations, integrated customer management and global business process integration. Surprisingly, companies do not treat corporate data as an asset, but rather focus on reactive quality management measures only. As a response to that, the chapter reports on the design of a reference model for Corporate Data Quality Management (CDQM). Following the principles of Design Science Research (DSR), the design process involved professionals of fourteen corporations headquartered in Germany and Switzerland. The reference model consists of six design areas which altogether comprise fifteen goals and 43 related practices. It supports practitioners during the establishment and optimization of their CDQM initiatives.
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Selvi, Ihsan Hakan, Orhan Torkul, and Ismail Hakki Cedimoglu. "An Integrated Grey Relations Analysis and VIKOR Method for Multi Criteria Decision Making under Fuzzy Environment." In Intelligent Techniques for Data Analysis in Diverse Settings, 228–51. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-5225-0075-9.ch011.

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Today, suppliers of companies are no longer local. Companies have to offer their products to the market just in time and as fast as possible in order to compete. This situation is possible by establishing an effective supply chain for the goods and services they need in the manufacturing system. Finding the right suppliers who are able to provide the companies with the high quality products and services at the reasonable price, at just on time and in the right quantities is an important issue concerned in the process of supply chains concept. There are certain techniques developed in this respect. Some of such methods are approaches developed for situations unmindful of fuzziness and vagueness. Nonetheless, the process of supplier selection contains both vagueness and fuzziness. This study improves the Grey Relational Analysis and VIKOR methods, to fuzzy and ambiguous environments. Then, these approaches are applied to a supplier selection problem, which is previously solved through fuzzy logic and AHP method in literature, and the comparative results of both techniques are given.
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Ullah, Asad, and Mohd Adil. "Service Quality in Supply Chain." In Innovative Solutions for Implementing Global Supply Chains in Emerging Markets, 173–86. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9795-9.ch012.

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In manufacturing industries or the supply chain, very few attempts have been made in the past to measure service quality or to test the linkages between service quality with supplier's satisfaction and loyalty. Thus, to fill the existing void in the literature, an attempt has been made to conceptualise a model proposing linkages of service quality with supplier's satisfaction and loyalty in the supply chain of automotive industry. The research design for this paper includes a combination of literature review and a survey of 220 and 170 practitioners from four and two automobile manufacturing companies located in Northern India and Western India, respectively. Structural Equation Modelling Techniques (SEM) has been used to examine the relationships among the variables and to test the goodness fit of the proposed model. Set of propositions related to model was empirically tested at supplier-manufacturer dyad and with an optimum fit of model, found that the data fits the model.
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Pal, Kamalendu. "Building High Quality Big Data-Based Applications in Supply Chains." In Supply Chain Management Strategies and Risk Assessment in Retail Environments, 1–24. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3056-5.ch001.

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Global retail business has become diverse and latest Information Technology (IT) advancements have created new possibilities for the management of the deluge of data generated by world-wide business operations of its supply chain. In this business, external data from social media and supplier networks provide a huge influx to augment existing data. This is combined with data from sensors and intelligent machines, commonly known as Internet of Things (IoT) data. This data, originating from the global retail supply chain, is simply known as Big Data - because of its enormous volume, the velocity with which it arrives in the global retail business environment, its veracity to quality related issues, and values it generates for the global supply chain. Many retail products manufacturing companies are trying to find ways to enhance their quality of operational performance while reducing business support costs. They do this primarily by improving defect tracking and better forecasting. These manufacturing and operational improvements along with a favorable customer experience remain crucil to thriving in global competition. In recent years, Big Data and its associated technologies are attracting huge research interest with academics, industry practitioners, and government agencies. Big Data-based software applications are widely used within retail supply chain management - in recommendation, prediction, and decision support systems. The spectacular growth of these software systems has enormous potential for improving the daily performance of retail product and service companies. However, there are increasingly data quality problems resulting in erroneous tesing costs in retail Supply Chain Management (SCM). The heavy investment made in Big Data-based software applications puts increasing pressure on management to justify the quality assurance in these software systems. This chapter discusses about data quality and the dimensions of data quality for Big Data applications. It also examines some of the challenges presented by managing the quality and governance of Big Data, and how those can be balanced with the need of delivery usable Big Data-based software systems. Finally, the chapter highlights the importance of data governance; and it also includes some of the Big Data managerial practice related issues and their justifications for achieving application software quality assurance.
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Conference papers on the topic "Supplier data quality"

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Chiang, Ching-Yi, and Ming-Hung Shu. "Supplier evaluation with quality-based fuzzy data." In 2009 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2009. http://dx.doi.org/10.1109/ieem.2009.5373304.

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Deng, Erwin, Rachel Lee, and Chun Der Lee. "Maskshop data preparation and quality control: from supplier management viewpoint." In Photomask and NGL Mask Technology XIX, edited by Kokoro Kato. SPIE, 2012. http://dx.doi.org/10.1117/12.964097.

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Jones, Kerry. "Improved Quality Truck Castings." In ASME 2013 Rail Transportation Division Fall Technical Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/rtdf2013-4722.

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Component failure in bolsters and side frames remains a problem for both railroads and suppliers, causing expensive repairs and even derailments. To understand and combat this problem, an evaluation of the steel was required. Bolsters were obtained from several suppliers to evaluate the current state of Association of American Railroads (AAR) M-201 standard for Grade B+ cast steel. Charpy impact and tensile test samples were machined from critical areas of these castings and tested at an independent laboratory. Distinct differences were found in processes and in mechanical properties between some suppliers. Supplier names are not identified in this paper. Based on the chemical and mechanical testing results and data analysis, changes to AAR M-201 Grade B+ requirements have been proposed. Additional bolsters have been obtained for further testing. These bolsters will incorporate the proposed changes to the standard and the same mechanical testing will be performed on them to determine the effectiveness of the proposed changes. Full scale static or fatigue testing will be conducted on additional bolsters. A survey of scrapped bolsters and side frames from several railcar producers and reclaim operations was conducted to determine the leading causes of failures of components removed from service. These results form the basis for a database that can be used to identify failure trends.
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Hassanzadeh, Soheil, and Kai Cheng. "Manufacturing Supplier Selection in Cloud Manufacturing Context and its Implementation and Application Perspectives." In ASME 2016 11th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/msec2016-8572.

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Nowadays, many companies have decided to use other companies’ competencies and outsource part of their manufacturing and business processes to suppliers from abroad in order to reduce costs, improve quality of products, and offer better services to customers. On the other hand, this decision has faced organizations with new challenges. Organizations need to evaluate their supplier’s performance, and consider their weakness and strength to survive in high competitive markets. In addition, cloud manufacturing, as a powerful tool will likely enable small and medium sized enterprises (SMES) to move towards using dynamic scalability and ‘free’ available data resources in a virtual manner and to provide solution-based, value-added, digital-driven manufacturing service over the Internet. The research presented in this paper aims to develop a supplier selection framework in the context of cloud manufacturing. The paper will present the background and concept of supplier selection following by proposed framework which consisted of four modules, multi-criteria module, bidding module, optimization module, and learning module. Finally, web based supplier selection approach will be briefly presented as it is not the main aim of this paper.
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Cui, Yanhe, and Jun Yang. "Interval Estimation of Process Capability Indices Based on the Weibull Distributed Quality Data of Supplier Products." In 2018 5th International Conference on Dependable Systems and Their Applications (DSA). IEEE, 2018. http://dx.doi.org/10.1109/dsa.2018.00024.

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Banerjee, Ashis Gopal, Walter Yund, Dan Yang, Peter Koudal, John Carbone, and Joseph Salvo. "A Hybrid Statistical Method for Accurate Prediction of Supplier Delivery Times of Aircraft Engine Parts." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-47605.

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Aircraft engine assembly operations require thousands of parts provided by several geographically distributed suppliers. A majority of the operation steps are sequential, necessitating the availability of all the parts at appropriate times for these steps to be completed successfully. Thus, being able to accurately predict the availabilities of parts based on supplier deliveries is critical to minimizing the delays in meeting the customer demands. However, such accurate prediction is challenging due to the large lead times of these parts, limited knowledge of supplier capacities and capabilities, macroeconomic trends affecting material procurement and transportation times, and unreliable delivery date estimates provided by the suppliers themselves. We address these challenges by developing a statistical method that learns a hybrid stepwise regression — generalized multivariate gamma distribution model from historical transactional data on closed part purchase orders and is able to infer part delivery dates sufficiently before the supplier-promised delivery dates for open purchase orders. The hybrid form of the model makes it robust to data quality and short-term temporal effects as well as biased toward overestimating rather than underestimating the part delivery dates. Test results on real-world purchase orders demonstrate effective performance with low prediction errors and constantly high ratios of true positive to false positive predictions.
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Trainer, Asa, Thomas Hedberg, Allison Barnard Feeney, Kevin Fischer, and Phil Rosche. "Gaps Analysis of Integrating Product Design, Manufacturing, and Quality Data in the Supply Chain Using Model-Based Defintion." In ASME 2016 11th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/msec2016-8792.

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Advances in information technology triggered a digital revolution that holds promise of reduced costs, improved productivity, and higher quality. To ride this wave of innovation, manufacturing enterprises are changing how product definitions are communicated — from paper to models. To achieve industry’s vision of the Model-Based Enterprise (MBE), the MBE strategy must include model-based data interoperability from design to manufacturing and quality in the supply chain. The Model-Based Definition (MBD) is created by the original equipment manufacturer (OEM) using Computer-Aided Design (CAD) tools. This information is then shared with the supplier so that they can manufacture and inspect the physical parts. Today, suppliers predominantly use Computer-Aided Manufacturing (CAM) and Coordinate Measuring Machine (CMM) models for these tasks. Traditionally, the OEM has provided design data to the supplier in the form of two-dimensional (2D) drawings, but may also include a three-dimensional (3D)-shape-geometry model, often in a standards-based format such as ISO 10303-203:2011 (STEP AP203). The supplier then creates the respective CAM and CMM models and machine programs to produce and inspect the parts. In the MBE vision for model-based data exchange, the CAD model must include product-and-manufacturing information (PMI) in addition to the shape geometry. Today’s CAD tools can generate models with embedded PMI. And, with the emergence of STEP AP242, a standards-based model with embedded PMI can now be shared downstream. The on-going research detailed in this paper seeks to investigate three concepts. First, that the ability to utilize a STEP AP242 model with embedded PMI for CAD-to-CAM and CAD-to-CMM data exchange is possible and valuable to the overall goal of a more efficient process. Second, the research identifies gaps in tools, standards, and processes that inhibit industry’s ability to cost-effectively achieve model-based-data interoperability in the pursuit of the MBE vision. Finally, it also seeks to explore the interaction between CAD and CMM processes and determine if the concept of feedback from CAM and CMM back to CAD is feasible. The main goal of our study is to test the hypothesis that model-based-data interoperability from CAD-to-CAM and CAD-to-CMM is feasible through standards-based integration. This paper presents several barriers to model-based-data interoperability. Overall, the project team demonstrated the exchange of product definition data between CAD, CAM, and CMM systems using standards-based methods. While gaps in standards coverage were identified, the gaps should not stop industry’s progress toward MBE. The results of our study provide evidence in support of an open-standards method to model-based-data interoperability, which would provide maximum value and impact to industry.
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Gower, Stephen R., and Derek C. Allen. "Safe and Successful Isolations and Interventions." In 2014 10th International Pipeline Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/ipc2014-33087.

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Pipeline isolations and interventions using hot taps and in-line isolation tools are used widely across the oil and gas industry for the maintenance of pipelines, platforms and process plants. They may also be used to facilitate tie-ins for the connection of new facilities or the diversion of operating pipelines. They require a clear understanding of risk and the factors that can lead to failure, which can have a safety, environmental or business impact affecting both the operator and supplier. A fresh look at the risks and how they can be effectively managed was carried out. The reviews showed that whilst there was a strong emphasis on personal safety and technical standards there was a need to maintain an emphasis on overall process safety. Using a global contract for the provision of services for isolations and interventions BP has worked closely with leading Suppliers (Furmanite, STATS Group, TD Williamson, TEAM Industrial Services) in this area to develop a framework for driving improvement and consistent delivery of these services. The work builds on some of the best practices developed with improving success rates with In-Line Inspection (ILI) and develops the process from the definition of safe and successful isolations through to the importance of capturing lessons learnt. The paper develops the processes for the definition of safe and successful isolations and interventions by addressing: • Definition of success • The engagement process and requirements for information. • Development of a common risk model based on failure data across all of the Suppliers • Use of effective quality management systems and key performance metrics • Development of an industry competency framework for technicians • Use of a clear lessons learnt process and the importance of performance reviews. Safe and successful isolations and interventions require effective management, clear communication and systematic engagement. They are achieved through a relationship between the operator and the supplier that is built on trust, open conversation and a willingness to improve; where both operator and supplier work together with common objectives and a common understanding of risk. The process outlined in this paper creates an opportunity to raise standards across the industry, building on knowledge, experience and best practices.
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Roelofsen, Julia, Stefan Fuchs, Daniel Fuchs, and Udo Lindemann. "Enabling an Internal Process Benchmark Using the Analysis of PDM-Data." In ASME 2008 9th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2008. http://dx.doi.org/10.1115/esda2008-59459.

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Today’s development-processes are mainly driven by three factors: time, quality and costs. High quality products need to be brought to the market in as little time as possible with competitive low costs. In addition to this, development processes need more flexibility and creativity in order to meet fast changing market requirements. With these factors competing, ways need to be found for an optimal process of developing products [1]. In this contribution the theoretical background of a tool that enables an internal process benchmark is introduced. This tool will be implemented at an international automotive supplier company in order to show potential for process improvement. The internal benchmark enables the identification of best practice processes that help to shorten time to market. The tool uses objective PDM-data to analyse processes instead of the often used interviews or observations, which are a more subjective source for process data. Main points of investigation in the analysis tool are CAD-drawings, change-requests, notify-and responsibility-lists. For example the time it takes from the generation of a drawing to its release for production is analysed; another example is the number of drawings generated per person. The analysis can be carried out concerning different locations, different customers or different departments and thus enables a company-wide benchmark of the workflow implemented in the PDM-system. All results are visualised by charts, which have to be interpreted in order to be used for the identification of best practice processes. To support the interpretation of the development-process-analysis and to draw conclusions for corrective or investigative actions, a portfolio is generated. This portfolio provides information about optimal values of the process performance figures and gives hints to why low or high values (e.g. in the number of drawings generated per department) can occur.
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Sadeh, Norman M., David W. Hildum, Stephen F. Smith, Dag Kjenstad, Thomas J. Laliberty, and John McA’Nulty. "Integration of Process Planning and Production Scheduling for Agile Manufacturing: A Case Study." In ASME 1997 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/detc97/dfm-4330.

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Abstract As companies increasingly customize their products, move towards smaller lot production and experiment with more flexible customer/supplier arrangements, such as those made possible by Electronic Data Interchange (EDI), they increasingly require the ability to (1) respond quickly, accurately and competitively to customer requests for bids on new products and (2) efficiently work out supplier/subcontractor arrangements for these new products. This in turn requires the ability to (1) rapidly convert standard-based product specifications into process plans and (2) quickly integrate process plans for new orders into the existing production schedule to best accommodate the current state of the manufacturing enterprise. This paper describes IP3S, an Integrated Process Planning/Production Scheduling shell for agile manufacturing. IP3S utilizes a blackboard architecture that supports (1) concurrent development and dynamic revision of integrated process planning/production scheduling solutions, (2) maintenance of multiple problem instances and solutions, (3) flexible user-oriented decision making, (4) declarative representation of control information, (5) the use of a common representation for exchanging information, (6) coordination with outside information sources and (7) portability and ease of integration with legacy systems. IP3S has been validated in the context of a large and highly dynamic machine shop at Raytheon’s Andover manufacturing facility. Empirical results show an average performance improvement of 23% in solution quality over a decoupled approach to building process planning/production scheduling solutions.
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