Automated Algorithmic Systems: Organization and

Implementation Guidelines

Husan Baqoyev

, Ilyos Kalandarov

, Alisher Khojiev

, Bakhriddin Bozorov

, Nodirbek Namozov

and Khosiyat Shermatova

Navoi Innovations University, Navoi, Uzbekistan

Navoi State University of Mining and Technologies, Navoi, Uzbekistan

Keywords: Automated System, Algorithmic Model, Information Part, Operational Part, Software Packages.

Abstract: The paper explores the feasibility of developing an algorithmic system from multiple sets, proposing the

involvement of six banks in the software construction process. This algorithmic approach is applied to design

and regulate production systems through algorithms for analysing and synthesizing abstract control systems.

Within the algorithmic framework for formalizing production system control processes, a bank constitutes an

independent functional unit comprising two components: information and operational. The information

segment stores numerical or symbolic data in predetermined languages (permanent information), while the

operational segment houses program packages that manipulate the information arrays within the bank.

1 INTRODUCTION

Applying the substitution rule, we structure the

system's components into distinct banks: the attribute

bank, comprising an informational hierarchy; the

model bank, consisting of informational relations

between task attributes and models, alongside

operational tasks such as model selection and

synthesis; and the algorithm bank, containing

information on computability features and

algorithms, along with operational tasks like selection

and optimization.

Additionally, we have the application software

package bank, encompassing algorithm/module

relations and operational tasks such as software

generation and testing. The operational bank, crucial

for system management, includes hierarchical

software modules and performs tasks like user

interaction and system recovery. Finally, the data

bank comprises network-structured databases

managed by a database management system,

facilitating standard data operations (Yusupbekov et

al 2021, Kalandarov 2022).

Incorporating algorithmic principles into object

control is a key aspect of this system's functionality.

Within the application package bank, software-

controlled control systems find their place, utilizing

the operational, application package, and data banks

during operation. The algorithmic scheme outlined in

prior research addresses both design and control

aspects of manufacturing systems. This scheme

underscores the role of software in controlling

manufacturing processes, emphasizing the reliance

on operational, application package, and data banks

for effective functionality (Vakhromeev et al 2023,

Igamberdiev et al 2022).

The system's architecture delineates distinct

banks, each with informational and operational

components. Notably, the application of

algorithmicizing principles extends to object control,

particularly within the application package bank. This

entails reliance on operational, application package,

and data banks for system operation. The proposed

algorithmic scheme provides formalisation for

manufacturing system control, integrating design and

operational considerations. Overall, the system's

effectiveness relies on the seamless interaction

between its constituent banks, facilitating efficient

management and control.

2 RESEARCH METHODOLOGY

To tackle control issues, a proposed algorithmic

scheme streamlines operations through four banks:

the feature bank, application package bank, data

752

Baqoyev, H., Kalandarov, I., Khojiev, A., Bozorov, B., Namozov, N. and Shermatova, K.

Automated Algorithmic Systems: Organization and Implementation Guidelines.

DOI: 10.5220/0012915300003882

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 2nd Pamir Transboundary Conference for Sustainable Societies (PAMIR-2 2023), pages 752-755

ISBN: 978-989-758-723-8

bank, and operational bank. Within each component,

the operational part dictates operations and rules for

executing tasks over the complex logical structure of

the information part. Access to this information is

facilitated from the operational section of the bank,

ensuring efficient management and control.

The algorithmic approach simplifies control

processes by organising functionalities into distinct

banks. The feature, application package, data, and

operational banks collectively regulate tasks and

operations within their respective domains. Each

bank's operational segment governs the execution of

rules and operations over the intricate logical

structure of its information counterpart, ensuring

systematic control and management of resources.

3 RESULT AND DISCUSSION

3.1 Essentials of Bank Functions and

Characteristics

The bank of operations serves as the central

component within the algorithmic system, facilitating

dialogue with users, managing operational aspects of

system banks, initializing the system, and recovering

from failures. It follows a five-stage process

comprising system initialization, feature selection,

task model selection, software configuration, and

execution. During operation, the operational bank

orchestrates instructions' sequence and manages

system bank components. Essential elements within

the operational bank include a monitor overseeing

system operations, an input language processor

engaging in user dialogue, and a sign bank. The

monitor encompasses a kernel, operational bank

monitors, a scheduler, and a calculator.

Embedded within the operational bank, the input

language processor incorporates syntactic and lexical

parsers for the input language, a dialogue monitor,

and an output instruction generator. These

components collectively enable seamless interaction

between users and the system, facilitating effective

communication and task execution. The robust

structure of the operational bank ensures systematic

control over the algorithmic system's functionality,

from user engagement to task completion, while

maintaining adaptability to handle unforeseen

challenges or system failures efficiently.

Figure 1: Optimizing Bank Functionality: Operational

Structure Essentials.

The attributes within the task bank enable the

identification of required models and algorithms for a

given system based on acceptable attribute groups,

facilitating the selection of suitable programs.

Figure 2: The Essence of Feature Banks: Structural

Frameworks and Informational Aspects.

At the outset, the system development process is

defined by attributes such as production type and

system components. These attributes guide the

categorisation of system components into task

classes, including planning, analysis, input-output,

and control and regulation. Planning involves daily

assignment compilation and technological route

optimisation, while analysis focuses on order flow

and machine operation. Input-output tasks manage

information exchange on equipment status and shift

assignments. Control and regulation tasks involve

loading production programs and overseeing

operations. Further detailing occurs at subsequent

levels, with planning tasks acquiring auxiliary

attributes defining optimisation criteria, and the fifth

level offering specific values for criteria such as

production time, equipment loads, and profit.

System operation begins with initialisation and

identification of technical configurations. The control

monitor kernel loads operational bank components,

including the scheduler and dialogue monitor. User

identification and access rights verification occur in

dialogue mode, followed by control transfer to the

Automated Algorithmic Systems: Organization and Implementation Guidelines

753

dialogue monitor. A structured "Menu Selection"

dialogue governs user-system interactions. A tailored

non-procedural language facilitates problem

articulation, with syntax designed to match the

control subject area. Predicates, expressed through

Russian inductive sentences, form co-occurring

formulations, with action preceding a list of goals

representing unknowns. Syntactic rules' keywords are

specified by users within the subject area, ensuring

task formulations adhere to Russian grammar and

meet syntactic requirements.

3.2 Software Suite: A Comprehensive

Selection for All Banking Needs

Models of tasks and technological processes are

stored in the module bank as operation tables. The

control system of this module bank analyses

interactions with operating personnel, creating a

general control system model. Tasks are categorised

into operational planning, control, and analysis

groups. Planning models and optimisation criteria are

defined for each task type, tailoring input and output

forms for operational and management levels. These

forms enable efficient database utilisation by

displaying non-overlapping details.

Depending on production nature and planning

methods, a production situation analysis model is

selected. The resulting control system's conceptual

model undergoes analysis to establish computational

schemes and data access methods. Algorithms are

chosen based on efficiency criteria, transforming the

conceptual model into a computational scheme, with

defined data access schemes, facilitating dialogue-

mode information exchange.

The conceptual model is stored in the application

software package bank's information section,

generating software based on computational schemes

and data access plans. The generated software is

transferred for operation. The application package

bank's information section includes library sets

containing source and object images, program data

sheets, and sets for visual and tabular output forms.

This systematic approach ensures efficient software

generation tailored to specific user needs, enhancing

operational effectiveness and facilitating information

exchange in dialogue mode.

3.3 Decoding the Data Bank: Insights

and Discoveries

The databank comprises organisational list data

structures, detailed in the system feature bank. Its

initial data volume varies depending on task scope.

Primarily, the databank buffers data, bridging time

gaps between solved tasks, and serves as central

storage, ensuring information reliability and validity.

A Database Management System (DBMS) is utilised

as a software tool. Implementing a DBMS

standardises data input-output and facilitates

presentation via program modules, ensuring

information consistency and reliability.

Figure 3: Inside Compass: Understanding Its Database

Management Structure.

The Algorithmic Process Information System

utilises the Compass Database Management System,

comprising schema, fragment, and related schema

translators, alongside a data manipulation language

pre-processor, autonomous access module, utility

group, and resident executive system. At its core, the

resident executive system incorporates the Compass

archive system, resident database management

system, and CMPSA administrative process monitor.

The system's information segment consists of data

structured and utilised within the information

system's functional framework, where stored fields

represent the smallest data units, stored records

comprise related fields, and stored files consist of

records of the same type. Adopting a full network

structure approach in its conceptual model, Compass

also incorporates service tools for system

administration, initiated through dialogue-based

commands at the terminal.

Service tools within the Compass Database

Management System are activated via specific

commands issued in dialogue mode from the

terminal. These tools are categorised into groups

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facilitating various functions. The initial group

permits retrieval of reference information, while

subsequent commands manage data exchange

between databases and the operating system,

including loading and copying data. Additional

commands cater to tasks such as cataloguing,

password management, structural modifications to

data storage, and information compression. Further

utilities handle tasks like initialising the database

dictionary, dumping and restoring the database, as

well as printing data, collectively enhancing the

system's administrative capabilities.

4 CONCLUSION

The described algorithmic technological information

system offers a versatile solution for managing

discrete production environments. By providing

interactive dialogue tools, developers can efficiently

design and construct control systems in their

preferred language and mode. The system's bank of

applied programs facilitates functions such as

analysing functioning tables, optimizing processes,

planning equipment schedules, maintaining

operational production models, and synthesizing

functioning tables. This comprehensive approach

empowers users to address various production

challenges effectively.

With its focus on achievability and persistence,

the system enables precise decision-making in

planning and management tasks. By integrating

algorithmic models, it streamlines production control

and enhances overall efficiency. The interactive

nature of the system fosters user convenience,

allowing for seamless adaptation to diverse

production environments. Overall, this technology

represents a significant advancement in shop floor

control systems, offering a sophisticated yet user-

friendly solution for optimizing production processes

and improving performance.

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