scholarly journals INFORMATION SYSTEM AND PRODUCTION PROCESS CONTROL

Author(s):  
Angelo Zanella ◽  
Egidio Cascini

We start with the definition of experimental data. First place we consider the controllable variables, whose levels are established by technical production experts with regard to a theoretic “model” defining the production components, their connections and working rules in sight of the envisaged achievements. Then, the responses or results of production activities, which typically show random variability. The controllable variables are used to regulate the means of their distributions and aspects of variability (Taguchi approach). An information system represents a data collection, which is directed to specific purposes like: financial control, accounting control, personnel control, business control, production control, framed around production programs, control of production lines and related maintenance, quality control, framed around control of nonconformities regarding some specification limits and ensuring product good quality over time. Qualitative guidelines for choosing the data for a quality control information system are that it must be as near as possible to a sufficient system which means that it is capable of explaining any nonconformity in a product characteristic, as well as being complete, that is, such that it is also capable of suggesting how to remove them. In a natural way quality control implies a dynamic approach based on a systematic improvement of production activities, starting from specific reference conditions. We consider two examples appropriated to explain the fundamentals of a methodology useful to cope with this complex subject. The first example refers to a real industrial application regarding the process control of polyvinyl chloride production, found in literature [9]. The second example concerns the distribution process of perishable goods, which is considered to be an innovation. In this case we suppose that there is a finite set of operating situations (points of sale) and that we can define an indicator Q=Q1 /c = Quality of a reference product/a corresponding economic quantity (cost or earning). In the case considered, by means of the ordering of the ratios total cost/total earning, we come to the most profitable situation.

Author(s):  
Angelo Zanella ◽  
Egidio Cascini

We start with the definition of experimental data. First place we consider the controllable variables, whose levels are established by technical production experts with regard to a theoretic “model” defining the production components, their connections and working rules in sight of the envisaged achievements. Then, the responses or results of production activities, which typically show random variability. The controllable variables are used to regulate the means of their distributions and aspects of variability (Taguchi approach). An information system represents a data collection, which is directed to specific purposes like: financial control, accounting control, personnel control, business control, production control, framed around production programs, control of production lines and related maintenance, quality control, framed around control of nonconformities regarding some specification limits and ensuring product good quality over time. Qualitative guidelines for choosing the data for a quality control information system are that it must be as near as possible to a sufficient system which means that it is capable of explaining any nonconformity in a product characteristic, as well as being complete, that is, such that it is also capable of suggesting how to remove them. In a natural way quality control implies a dynamic approach based on a systematic improvement of production activities, starting from specific reference conditions. We consider two examples appropriated to explain the fundamentals of a methodology useful to cope with this complex subject. The first example refers to a real industrial application regarding the process control of polyvinyl chloride production, found in literature [9]. The second example concerns the distribution process of perishable goods, which is considered to be an innovation. In this case we suppose that there is a finite set of operating situations (points of sale) and that we can define an indicator Q=Q1 /c = Quality of a reference product/a corresponding economic quantity (cost or earning). In the case considered, by means of the ordering of the ratios total cost/total earning, we come to the most profitable situation.


Author(s):  
A. Popov ◽  
O.N. Lopateeva ◽  
A.K. Ovsyankin ◽  
M. M. Satsuk ◽  
A. A. Artyshko ◽  
...  

Among the measures aimed at the effective performance of public services in a modern urban environment, one of the main is the quality control and efficiency of the work performed. Timely street cleaning is hampered by several groups of problems, including the lack of a single automated information system (AIS) control of the work performed. In this regard, there is a need to improve and automate this area. This approach will allow you to combine high performance due to the speed of the system and effective quality control of street cleaning. The purpose of this work is the study and analysis of existing information systems (is), allowing to automate the process of quality control and operational performance of the above tasks. On the basis of the conducted researches, to develop is, having coordinated with the customer (administration of the Central district of Krasnoyarsk) requirements and functionality which allow to automate this process.This article presents the main aspects of the design and software solutions for the implementation of the algorithm in the form of AIS, designed to automate the process of monitoring the cleanliness of streets in the city. The development of AIS was conducted in the PhpStorm integrated development environment in the PHP programming language.


2013 ◽  
Vol 467 ◽  
pp. 277-281
Author(s):  
Shao Ning Han ◽  
Hong Wang ◽  
Hang Wu ◽  
Pi Song Sun ◽  
Yu Hui Xue ◽  
...  

According to Chinese traditional classification, large-sized jackets weight over 10,000 tons and stand in over 100-meter water. Large-sized jackets are different from the normal in construction tonnage, structural dimension and quality control requirements as well as construction difficulty. More complicated construction technology and programme, higher grade of materials, stricter control requirements on node weld and higher risks all need matched stricter, more meticulous and more comprehensive management in planning and scheduling. Combined with construction of LW3-1 deep-water jacket, this paper describes the planning, tracking progress, process control and optimization.


CATENA ◽  
2008 ◽  
Vol 75 (2) ◽  
pp. 200-215 ◽  
Author(s):  
Severin Hohensinner ◽  
Mathew Herrnegger ◽  
Alfred P. Blaschke ◽  
Christine Habereder ◽  
Gertrud Haidvogl ◽  
...  

1989 ◽  
Vol 5 (03) ◽  
pp. 188-199
Author(s):  
Paul C. Powell ◽  
Charles I. Zigelman

This paper describes how a formal manufacturing environment, as defined by the American Production and Inventory Control Society (APICS), compares with modern shipbuilding techniques. Formal manufacturing, through a product-based build strategy, provides a framework for integrating contract scheduling, design development, material purchasing, inventory control, production capacity planning, and production control. An understanding of formal manufacturing provides a foundation for understanding modern shipbuilding techniques.


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