Contributing Hebrew Name Headings to NACO: A Participant's View

1994 ◽  
Vol 8 (1) ◽  
pp. 61-68
Author(s):  
Rachel Simon
Keyword(s):  
Quality Control ◽  
Production Data ◽  
University Libraries ◽  
Princeton University ◽  
The Future ◽  
Enhance Efficiency

Princeton University Libraries have undergone several phases over the years regarding authority work. This paper focuses on Princeton's treatment of Hebrew name headings within the framework of authority work in general, prior to and following the library's involvement in the NACO (National Coordinated Cataloging Operations) project. The paper deals with the following topics: the methods used at Princeton for authority work before the involvement with NACO in 1980; the stages of Princeton's involvement with NACO after 1980 (including production data); procedures developed at Princeton to facilitate authority work, enhance efficiency, and guarantee quality control in all production levels; personnel involved in authority work; the process undertaken to become an independent contributor of Hebrew name headings; the workflow of Hebrew name headings and the principles applied in establishing Hebrew name headings; and plans for the future.

Interviews with collection development managers

2015 ◽  
Vol 34 (4) ◽  
pp. 134-135
Author(s):  
Kay Ann Cassell
Keyword(s):  
Design Methodology ◽  
Collection Development ◽  
University Libraries ◽  
Yale University ◽  
Content Type ◽  
Princeton University ◽  
Development Officers

Purpose – The purpose of this paper is to present interviews of two collection development managers: David Magier, Princeton University and Daniel Dollar, Yale University. Design/methodology/approach – The approach was interviews. Findings – These interviews showed what goes into the thinking of collection development officers in large university libraries. There are probably more similarities than differences. Originality/value – This is the first of a series of interviews with collection development managers.

scholarly journals ANALISIS KUALITAS PRODUK MENGGUNAKAN METODE STATISTIC PROCESS CONTROL (SPC) MINITAB DAN TIME-CHARTING DI PT. COCA-COLA BOTTLING INDONESIA UNIT LAMPUNG

2017 ◽  
Vol 1 (2) ◽  
Author(s):  
Joko Saryono ◽  
Keyword(s):  
Quality Control ◽  
Process Control ◽  
Statistical Process Control ◽  
Control Method ◽  
Production Data ◽  
Statistical Process ◽  
Research Results ◽  
Statistic Process Control ◽  
Gas Volume ◽  
A Company

Abstract PT. COCA-COLA BOTTLING INDONESIA is a company engaged in the field of Agro-industry is bottling soft drinks and not sparkling. The products produced are Coca-Cola, Sprite, Fanta, and Tea. To be able to compete with similar industries then the company implements quality control by Statistical Process Control method. In the development of this SPC many methods there are manual or who use the software. Currently PT. Coca-Cola Bottling Indonesia in quality control using Time Charting method, but since the transition from Minitab to Time Charting the tendency of the value of capability below standard, whereas production data is almost the same as using Minitab. The purpose of this research is to analyze the inequality of Statistical Process Control between Minitab 13 and Time Charting. Time Charting method is a new method that is given by the headquarters for the process of quality control can be fast and accurate. Quality control with the Statistical Process Control of Minitab and Time Charting methods after the results of the research results was found to be part of different LSL and USL charging, and Calculate Statistic Using different from Minitab method should still be 6 but in written procedure 3. For writing LSL And USL if the Time Charting is determined by the head office while Minitab analysts fill in based on experiments on the decrease of gas volume marketed in previous years. From the research results obtained Cpk data for Minitab method 13 is Sprite 390 ml 1.47, Sprite 1000 ml 1.90 and Sprite 1500 ml 1.38. The result of the research was using Minitab method and the Charting Time of Capacity that is above 1.33 average. The causes of the resulting inequality of both methods are the LSL, USL and Calculate Statistic Using values. The smaller the value of Calculate Statistic Using the higher Cpk produced. Keywords: Production, Statistical Process Control, Quality.

The Establishment and Management of a Production Data Exchange Group

2005 ◽  
Vol 21 (02) ◽  
pp. 73-80
Author(s):  
Gregory F. Morea
Keyword(s):  
Data Exchange ◽  
Production Data ◽  
Computer Assisted ◽  
Product Model ◽  
Aircraft Carrier ◽  
Exchange Group ◽  
Digital Format ◽  
Marine Industry ◽  
The Future ◽  
Design And Construction

The design and construction of any marine vessel designed on a computer-assisted design (CAD) system, from a nuclear aircraft carrier to the smallest work boat, requires the interaction of many electronic databases, all of which must be continually updated for the work to proceed. The exchange of this information, especially geometry, in digital format is accomplished using many different tools and techniques. Much has been presented to the marine community about the tools used, such as the Initial Graphics Exchange Specification (IGES) and the Standard for the Exchange of Product Model Data (STEP), and how these tools might be used for exchanges in the future, but little has been presented on how production data exchanges actually occur. At Electric Boat, current submarine programs cannot wait for future data transfer solutions. Design and construction data must be exchanged among various activities, internal and external, with such volume as to make manual reentry of data an unrealistic solution. Because of the complexities associated with the electronic exchange of these data, the General Dynamics (GD) Marine organization of Electric Boat has a dedicated group that both performs production data exchanges and researches and implements new methods of electronic transfer. This paper discusses the rationale for and the formation of the data exchange group at Electric Boat, along with its place within GD Marine. It then presents an overview of the tools used by the group and how production transfers occur, both routine and unique. Notable transfers provide examples of how the group works to solve transfer problems. Importantly, this paper shows how many of the exchange standards developed for the marine industry actually work in production. Special emphasis will be placed on the exchange of solid models in a day-to-day environment. The paper concludes with a look at the future of production data exchanges for Electric Boat and the larger marine industry.

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