LECTURE-3

Lets remember about Elements of a System and Characteristics of a System

OBJECTIVE OF TODAY’S LECTURE

Today we will discuss about calcifications or type of systems and another events of system within which one views a system is related to the use of the systems approach for analysis.

THE MAINE POINTS OF TODAY’S LECTURE

TYPES OF SYSTEM

SUBSYASTEMS

SUPERSYSTEMS

CONTROL IN SYSTEMSCHECKING THE SYSTEM

MODELING

ATTRIBUTES OF MODELING

SIMULATION

TYPES OF SYSTEM

Systems have been classified in different ways.

Common calcification are:-

1) Physical or abstract.

2) Open or closed.

3)Natural or man-made information systems

Physical SystemsPhysical systems are tangible entities that may be static or dynamic in operation. For example, the physical parts of the computer center are the offices, desks, and chairs that facilitate operation of the computer . They can be seen and counted; they are static. In contrast, a programmed computer is a dynamic system. Data, programs, output, and applications change as the user’s demands or the priority of the information requested changes

Abstract SystemsAbstract systems are conceptual or nonphysical entities. They may be as straight forward as formulas of relationship among sets of variables or models-the abstract conceptualization of physical situations. A model is an easier way for the analyst to visualize relationships in the system under study. The objective is to point out the significant elements and the key interrelationships of a complex system.

Open or Closed Systems

Another classification of systems is based on their degree of independence. An open system has many interfaces with environment. The concept of used and open system are illustrated in it permits interaction across its boundary; it receives inputs from and delivers outputs to the outside. An information system falls into this category, since it must adapt to the changing demands of the user. In contrast, a closed system is isolated from environmental influences. In reality, a completely closed system is rare. In systems analysis, organizations, applications and computer's are invariably open-dynamic systems influenced by their environment.

A closed system is one that does not interface with its environment, i.e. it has no input or output. This concept is more relevant to scientific systems than to social systems. The nearest we can get to a closed social system would be a completely self-contained community that provides all its own food, materials and power, and that does not trade, communicate or come into contact with other communities.

Figure:4.1:- Concept of Closed and open System

Five important characteristics of open systems can be identified.

1) Input from outside:-Open systems are self-adjusting and self-regulating. When functioning properly, an open system reaches a steady state exhorts when goods are purchased and sold without being either out of stock or overstocked. An increase in the costs of goods forces a comparable increase in prices or decrease in operating costs. This response gives the firm its steady state.

2) Entropy:- All dynamic systems tend to run down over time, resulting in entropy or loss of energy. Open systems resist entropy by seeking new inputs or modifying the processes to return to a steady state.

3) Process, output, and cycles:-Open systems produce useful output and operate in cycles, following a continuous flow path.

4) Differentiation:-.Open systems have a tendency toward increasing specialization of functions and a greater differentiation of their components.

5) Equafinality:-The term implies that goals are achieved through differing courses of action and a variety of paths. In most systems, there is more of a consensus on goals than on paths to reach the goals.

Characteristics of Open Systems

SubsystemsFrom the preceding discussions, it has become apparent that each system is nested in a larger. The system in the hierarchy that we are most interested in studying or controlling is usually called "the system“ .The business firm is viewed as "the system" or the "total system" when focus is on production, distribution of goods, and sources of profit and income.

Smaller systems within the system are called subsystems. This distinction has important implications in practice with regard to optimization: people tend to optimize for the good of the (sub) system they are most closely related to rather than the whole system.

Super systems or supra systems is magnified part of a system. The business itself a subsystem of a super system known as country or society looking from the angle of income tax department, business system of is one system of their super system from where revenues are earned

Super system

CONTROL IN A SYSTEMS The basic model of a system as inputs, process, and outputs does not include regulation and control of the system.

For control proposes, a feedback loop is added to the basic model (Figure 4.2). In its simplest form, outputs from the system are compared with the desired output (standard), and any difference causes an input to be sent to the process to adjust the operations so that output will be closer to the standard.Figure 4.2- Controlling the parameter of a system

Feedback Control for a System. Feedback, which seeks to dampen and reduce fluctuations around the standard, reinforces the direction in which the system is moving. Positive feedback causes the system to repeat or amplify an adjustment or action. For example, a programming supervisor may have learned about the use of modular program structure. After trying it on a small project with good results (positive feedback), the supervisor tries it on a larger project, again with good results. . The supervisor may continue this until all programming is done in that way (a steady state ) or until projects are found for which it does not work.

An open control system is one with inputs, processes and outputs that have no connection or information flow from the process or outputs back to the inputs.

Figure 4.3 is a simple example. In the open-loop system the control depends on the inputs and the processes being correct. Nobody gathers data to compare actual sales and actual expenses with quotas and budgets.

Information Feedback Systems

An integral part of systems theory is the concept of automatic feedback control. This is particularly important for the study and design of management information systems because the theory and the practice of cybernation (feedback control) underlie all design and application of computers as well as of information systems that utilize them.

Figure:4.4:- Open-loop Control System

Negative Feedback controlNegative feedback control in a system means keeping the system operating within certain limits of performance. For example, an automated production system is in control if inputs of material and energy

are converted to output percentage of defective items falling within allowable limits. A system which is out of control allowable limits because the regulatory mechanisms are not operative. Control using negative feedback normally involves four elements:

1) A characteristic or condition to be controlled. The characteristic or condition must be measurable from some output.

2) A sensor for measuring the characteristic or condition.

3) A control unit which compares the measurements with a standard or that characteristic or condition.

4) An activating unit which generates a corrective input signal to the process.

Figure:4.5:- Closed-Loop Control System

CHACKING THE SYSTEM

There are three ways to get early feedback on the viability of the MIS just designed:

(1) Modeling

(2) Simulation

(3)Test planning

Their importance lies in the impact that early problem discovery was on project cost. A problem discovered at design time is much cheaper to in than is one found after the system has been put into operation. During our design efforts, we have quantified as much of the system as possible. We now attempt to determine quantitative ranges for inputs and outputs, quantitative relationships for the transfer functions, and time and reliability responses for operations for the transfer functions, and time and reliability responses for operations in the system. Decision models are developed in both mathematical equation form and decision table form. The purpose of modeling at this stage is to define the system more precisely and to improve it.

MODELINGModeling is the process of attempting to accurately characterize a physical phenomena by mathematical or logical relationships which can be programmed to run on a computer. Then, by generating the appropriate representative input data, we can use this model to simulate the real system and observe the responses to various input conditions .Models are important aids to thinking, creativity and communication and, as these are major preoccupations of the analyst, their relevance should be clear .The selection of an appropriate model requires flexibility and imagination, adopting a model relevant to the circumstances.

Figure-4.6:-Shows an outline of the way models are developed and used

ATTRIBUTES OF MODELING

Modeling demands the following conventions and attributes:-

2) Consistency

1) Simplicity

3) Completeness4) Precision

5) Hierarchy

Hierarchical models enable the Analyst to maintain several levels of detail in the constructed models. A high-level model will have little detail on it since its primary purpose is to highlight the most important features of the system.

ProcessGenerator

Random

Number

0.63

0

15 32 60

Random Number

Decision Variable

Demand Function

Figure:4.7:- Simulation of inventory

The term system simulation: refers to duplicating the essence of a system in a way that allows an

investigator to study and work with it. The mathematical or symbolic representation of a system is called the model .This approach to problem solving is not new; investigators have frequently; made models or representations of reality in order to learn, to test ideas, and to predict the effect of introducing changes. However, the computer has made possible systems studies that hereto were impractical. Even a modestly scaled system simulation usually requires more computations than can be efficiently performed by hand. Simulation is used in the sciences for simulating behavior and in business for simulating business systems.

SIMULATION