คู่มือการทำรายการทรัพยากรสารสนเทศตามระบบ WALAI AutoLib นี้ จัดทำขึ้นเพื่อเป็นมาตรฐานเดียวกันในการทำรายการทรัพยากรสารสนเทศ ระหว่างห้องสมุดทั้ง 4 แห่งในสังกัดสำนักวิทยบริการและเทคโนโลยีสารสนเทศ ได้แก่ ห้องสมุดกลางเทเวศร์ ห้องสมุดสาขาโชติเวช ห้องสมุดสาขาพระนครเหนือ และห้องสมุดสาขาพณิชยการพระนคร ข้อมูลความรู้ทั้งหมดเกิดจากการระดมสมองและแลกเปลี่ยนเรียนรู้ของหัวหน้าห้องสมุดและบรรณารักษ์ทุกคน ซึ่งบางคนมีประสบการณ์มานานจากโปรแกรมอัตโนมัติระบบอื่น ผสมผสานรวมกันกับข้อมูลของระบบอัตโนมัติ WALAI AutoLib ของมหาวิทยาลัยวลัยลักษณ์ หนังสือคู่มือเล่มนี้มีเนื้อหาประกอบไปด้วย หลักเกณฑ์การประทับตรา การลงทะเบียน การลงรายการ การพิมพ์บาร์โค้ด การติดสัน และการจำหน่ายออกทรัพยากรสารสนเทศของห้องสมุดในสังกัด มทร.พระนคร คณะผู้จัดทำขอขอบคุณคุณกมร สุประภารพงษ์ที่กรุณาเสียสละเวลาเป็นผู้รวบรวมและจัดพิมพ์เนื้อหาคุณสายธาร สุเมธอธิคมที่กรุณาออกแบบรูปเล่มให้อย่างสวยงาม รวมทั้งท่านอื่นๆที่กรุณาช่วยเหลือแต่มิได้เอ่ยนามไว้ ณ ที่นี้ทุกท่าน

The problem of this research is automotive part companies do not have order because of the world economic crisis and effect to automotive industry. Automotive and automotive parts demand in the world decrease. Automotive Industry of Thailand received affect. Automotive part companies cannot export to foreign markets. The companies in Thailand need the forecasting of automotive part quantity demanded by foreign markets by selecting the most accurate model. This paper presents the modeling for forecasting demand for automotive part of foreign markets to Thailand with time series forecasting techniques. In this study the automotive part are wheels and including parts and accessories because Thailand exported the most in group of automotive parts. These five countries have consistently demanded the largest number of wheels and including parts and accessories are Japan China South Korea Germany and Indonesia. The research involves historical collecting data for the period of 1997 to 2008. The evaluation function of forecast error is used with MAPE. The results reveal that each country suits for each model in term of the chosen dimension. The government can use the forecasting demand for effective production planning by informing manufactures.

The results revealed that the manager๛s opinions towards operation of quality control and inspection of auto-parts at a high level were lineworkers in car accessory production plant and other production plant. The opinions of the office workers towards operation of quality control and inspection of auto parts at a high level were lineworkers in car body production plant car accessory production plant and other production plant. When comparing the operation level of quality control and inspection of plants classified by types of vendors it was found that there was a significant difference at .05 level. The collected data were analyzed by SPSS program into percentage mean standard deviation t-test one-way ANOVA and multiple comparison.

This study aimed to use Poka-Yoke techniques to help prevent errors and reduce loss in Front Side Fender Model assembly process. The researchers used four tools in the 7QC tools which were Check Sheet Cause-and-Effect Diagram and Graphs to search for causes and ways to solve problems and Cause and Effect Matrix and ECRS Techniques. The study revealed that the main cause of the problems was that the incorrect assembled side fenders were submitted to another department. This mistake had bad effects on time and workforce spent for correcting work including more expenses. The mistakes occurred because there was no tool for detecting errors in the work piece. Therefore the researchers use Poka-Yoke techniques in order to decrease errors by designing a control system for target detection while it was moving through the process. After collecting data the study showed that before the improvement during January to August 2019 the number of problems caused by the process were 0.093. However the number of problems after the improvement during September to December 2019 reduced to 0. It was obvious that this improvement reduced the loss from the front side fender assembly process up to 100.

Develop a prototype of the smart bin for supporting solid waste management at the source. The objective is to develop the functionality of the smart bin to meet the requirements of users. A body design of the smart bin prototype made from plastic with a lid size 25 cm. x 36 cm. x 48 cm. the total volume of the smart bin was 31.5 kg and using ARM STM32F4 series micro controller to control the functions of the smart bin. There is a sensor to measure the temperature and humidity. Ultrasonic level sensor Infrared distance measuring sensor and weight sensor with load cell data display controlling the opening and closing of the smart bin by servo motor. A Smart bin prototype can show the amount of waste. Moreover the level of waste and the weight of the waste inside were showed. The smart bin was showed relative temperature and humidity values inside a bin. The optimum distance to the reflective object of the sensor for opening and closing the smart bin was in the range of 20-50 cm. The Smart bin lid provided approximately 7-9 seconds to maintain the status to lid open representing an average time of 7.4±0.9 seconds. This research will help promote waste management at the source and effectively benefits to solve the problem of waste accumulation in place.