Geometry unifies process control, production control and alarm management

2004 ◽  
Vol 15 (1) ◽  
pp. 22-27
Author(s):  
R. Brooks ◽  
R. Thorpe ◽  
J. Wilson
Keyword(s):  
Process Control ◽  
Production Control ◽  
Alarm Management ◽  
Control Production

scholarly journals INFORMATION SYSTEM AND PRODUCTION PROCESS CONTROL

2019 ◽  
Author(s):  
Angelo Zanella ◽  
Egidio Cascini
Keyword(s):  
Information System ◽  
Quality Control ◽  
Process Control ◽  
Production Control ◽  
Reference Conditions ◽  
Specific Reference ◽  
Theoretic Model ◽  
Perishable Goods ◽  
Control Production ◽  
Accounting Control

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.

scholarly journals INFORMATION SYSTEM AND PRODUCTION PROCESS CONTROL

2019 ◽  
Author(s):  
Angelo Zanella ◽  
Egidio Cascini
Keyword(s):  
Information System ◽  
Quality Control ◽  
Process Control ◽  
Production Control ◽  
Reference Conditions ◽  
Specific Reference ◽  
Theoretic Model ◽  
Perishable Goods ◽  
Control Production ◽  
Accounting Control

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.

Formal Manufacturing Approaches to Modern Shipbuilding

1989 ◽  
Vol 5 (03) ◽  
pp. 188-199
Author(s):  
Paul C. Powell ◽  
Charles I. Zigelman
Keyword(s):  
Inventory Control ◽  
Capacity Planning ◽  
Production Control ◽  
Production Capacity ◽  
Design Development ◽  
Manufacturing Environment ◽  
Control Society ◽  
Control Production ◽  
Production And Inventory Control

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.

Research on Visual Production Process Control System Oriented to Discrete Manufacturing

2011 ◽  
Vol 474-476 ◽  
pp. 1914-1919
Author(s):  
Wan Gao Li ◽  
Xiao Le Liu ◽  
De Chang Sun
Keyword(s):  
Control System ◽  
Process Control ◽  
Data Acquisition ◽  
Production Process ◽  
Web Application ◽  
Production Control ◽  
Process Control System ◽  
Seamless Integration ◽  
Event Tracking ◽  
Discrete Manufacturing

Firstly, the requirements of production control and the features of discrete manufacturing process were researched , the production process control system architecture was built. Then, the key technologies used in the system realization were studied. Automatic identification technology was used in data acquisition; product tracking and event tracking technologies were used to implement production monitor, abnormal monitor respectivly in application server; Web technology was used in production statistics and analysis in presentation layer. Data acquisition and statement analysis implementation were separately based on the Windows and Web application of NET platform; products tracing and event tracking implementtation were based on the configuration visual software platform: GE Cimplicity. Every layer is distinct and seamless integration in the entire system, the whole architecture has strongly robustness and expandability. Finally, a case proved the validity of this system.

Use of microelectronics to upgrade process control into production control

1983 ◽  
Vol 60 (2Part2) ◽  
pp. 443-447 ◽  
Author(s):  
C. B. von Klösterlein ◽  
H. J. Vos
Keyword(s):  
Process Control ◽  
Production Control

scholarly journals Perancangan Sistem Penjadwalan Dan Pengontrolan Produksi Perusahaan Padupadan

2019 ◽  
Vol 11 (2) ◽  
pp. 358-378
Author(s):  
Marsheilla Marsheilla ◽  
Marsheilly Marsheilly
Keyword(s):  
Production Scheduling ◽  
Production Control ◽  
Small And Medium Enterprises ◽  
Raw Material ◽  
Flow Diagram ◽  
Target System ◽  
System Control ◽  
Total Production ◽  
Local Product ◽  
Control Production

The development of garment industry, especially for export, may bring certain challenges to Micro Small and Medium Enterprises (MSME). The company that export its products has to handle its production carefully, in particular for the export deadline. When the company fail to deliver its products on time, a high amount of fine, approximately 30% of total production cost, will be faced. Padupadan is a garment focusing on local product. To be competitive, it needs to improve its quality in both scheduling and production control. Orders has been accepted without actual information status of running order which cause delay and low product quality. Due to that situation, this company needs a system that assist decision making relating to controlling orders and performance of any parties in production process.Case study was used as method of this explanatory research. Data were analyzed using MIT 90’s Framework and Data Flow Diagram. Design of Padupadan production system is related with 9 analyzed activities, namely marketing, sales order, production scheduling, human resource management, purchasing, receiving, warehouse (raw material), production, and warehouse (finished goods) which will be structured and standardized for the company. This system provides assistance in determining production scheduling target, system to control production that will help owner in evaluating employees, performance of production department and categorized supplier. Owner provides positive respon on the design since it can assist the company for future advance. Keywords: Scheduling System Control; Production Control

Computer-Based Management Information in a Small Company

1969 ◽  
Vol 184 (1) ◽  
pp. 397-408 ◽  
Author(s):  
B. Goulder ◽  
A. Moss ◽  
R. Shaw
Keyword(s):  
Production Control ◽  
Management Control ◽  
Small Company ◽  
Human Aspects ◽  
Machine Loading ◽  
Engineering Company ◽  
College Of Technology ◽  
Control Production ◽  
Computer Based ◽  
Flow Charts

The use of computers in the management of medium and large engineering factories is well established. This paper is concerned with the development of a system of management control in a small engineering company using a desk-sized computer on site and a medium-power computer at the local College of Technology. The system, though simple and relatively cheap, provides for production control by means of machine loading charts and exception reports of jobs overdue, cost control, quality control, production statistics and bonus computation. Systems flow charts and examples of output are included. Emphasis is placed on the human aspects of implementing the system, and the immediate effects of the system on the management of the company are discussed.

Tag Identification Protocols in RFID Systems

2013 ◽  
pp. 1-33
Author(s):  
Francesca Lonetti ◽  
Francesca Martelli
Keyword(s):  
Radio Frequency Identification ◽  
Public Transportation ◽  
Production Control ◽  
Tag Identification ◽  
Rfid Systems ◽  
Animal Identification ◽  
Control Production ◽  
Frequency Identification ◽  
And Performance ◽  
Application Fields

Fast and reliable identification of multiple objects that are present at the same time is very important in many applications. A very promising technology for this purpose is Radio Frequency Identification (RFID), which is fast pervading many application fields, like public transportation and ticketing, access control, production control, animal identification, and localization of objects and people. The problem approached in this chapter is the tag identification in RFID systems. This problem occurs when several tags try to answer at the same time to a reader query. If more than one tag answers, their messages will collide on the RF communication channel, and the reader cannot identify these tags. There are two families of protocols for approaching the tag collision problem: a family of probabilistic protocols, and a family of deterministic ones. In this chapter, the authors give an overview of the most important approaches and trends for tag identification in RFID systems and provide the results of a deep comparison of the presented tag identification protocols in terms of complexity and performance.

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