AUTOMATION OF DESIGNING FUNCTIONING PROCESSES
OF MAN-MACHINE SYSTEMS
Mikhail Grif, Yevgeny TsoY, ZHANG XIANKUI
Novosibirsk State Technical University, Novosibirsk, Russian Federation
Abstract: The paper presents a review of the authors´ monograph on the theory and
practice of optimal process design of man-machine systems (MMS) according to
efficiency, quality and reliability (EQR) indices on the basis of functional-structural
theory, artificial intelligence methods, and sequential variant analysis. It pools the
necessary information about the models, methods, technologies and software, applied
tools.
I. INTRODUCTION
Design of man-machine systems functioning processes (MMS FP) according to
efficiency, quality and reliability indices occupies an important place in the
automation of design work, object control and making decisions in various branches
of industry. The MMS class may be sufficiently wide: computerized process control
systems, computer-aided design systems, computer-aided research systems, operator
systems, systems of ergonomic research automation, etc.
National and foreign experience of MMS creation and development shows that
striving for increasing the adequacy of the employed models of MMS functioning
process due to the introduction of an increasing number of accountable factors, and
extension of the alternatives sets poses objective difficulties for choosing the optimal
variant of MMS FP execution. Thus the urgency of approaches to optimal design of
MMS functioning processes providing an opportunity for generation and fast analysis
of a sufficiently large number of alternatives increases.
In spite of a wide range of the MMS FP available (semi-Markov processes, formal
grammar, Petri nets, logical automata, logical-linguistic models, GERT and PERT
nets, functional and functional-semantic models), none of these is free of this or that
disadvantage and cannot be wholly used as a basis for the present-day MMS FP
design automation. Nevertheless, analysis of the models indicated shows that with
relation to the starting point, for further modernization and practical use in optimal
design, the functional-structural MMS theory and Prof. A.I. Gubinsky′s generalized
structural method are the most complex and prospective. In its invariable form, MMS
functional-structural theory has a number of limitations on its use in the optimal
design system:
 It is mostly based on the probability models for calculating EQR indices, with
the facilities for taking into account fuzzy data;
 It is mostly based on the structural analysis methods of functional and being
not available element system structure, which complicates modeling complex
(large) system;
 It does not contain facilities for transition to invariant optimization problem
statements for their most efficient solution.
The present work develops an approach to optimal design of MMS FP according to
efficiency, quality and reliability indices on the basis of the models of functional-
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structural theory, artificial intelligence and sequential variant analysis methods which
should lift the above restrictions.
The monograph is written on the basis of the authors′ original research. It contains
seven chapter.
II. PROBLEM STATEMENT
Chapter 1 of the monograph considers the major models, methods and technologies
for optimal MMS FP design according to probability and fuzzy indices of efficiency,
quality and reliability. Comparison of basic methods and models and
recommendations for their efficient use are given.
The MMS functioning process is understood as a logic-time sequence of actions and
operations of the ergatic and non-ergatic system elements resistant towards
disturbances and leading to achieving the goal (or goals) of functioning [1]. MMS FP
runs in inter-connected spaces: MMS elements E , executed functions F , MMS states
S , the occurring events W and MMS indices Q . The MMS FP optimization problem
statement is of the following form:
К EQR ( А)  extr,
(1)
A Md
where A is the variant of MMS FP execution; К EQR ( А) the optimality critetion
for the EQR criteria combination; M d a set of admissible alternatives. As the EQR
criteria, the probability of correct (error free) execution B(A) , mean time T (A) and
average expenses (profit) V (A) resulting from the execution, the probability of timely
~
realization of P( t  Td ) , fuzzy probability of correct realization of B( A) , fuzzy
~
~
expenses (profit) V ( A) and realization time T ( A) are applied.
III. SET OF ALTERNATIVES CONSTRUCTION
Chapter 2 describes the methods of MMS FP optimization model representation on
the basis of functional and functional-semantic net work with the application of MMS
element sets, executed functions and operations. Estimates of alternatives set power,
structural and object oriented design strategies as well as a method for obtaining a
unified knowledge base of MMS FP in the production-logical form are given.
The operation O  O( F , E, S , MW , Q)  MТФЕ is understood as a process of function F
performance by the element E in the state of MMS s. As a result, some antithetical
events W  MW can take place. Probable or (and) fuzzy indices EQR
Q(W )  fO ( F , E, П E , S ) are connected with each event W . As a “simple” operation,
there used standard functional units (SFU), “working operation” (WO), and two SFU
of condition testing: testing the performance correctness of the operation controlled
(“functional control” (FC)) and testing the equipment efficiency and (or) human
being’s ability to work (“diagnostic control” (DC)). While performing WO SFU A ,
two events are probable: W A1 as correct realization and W A0 as non-correct. Realization
of FC (DC) SFU  involves four events: W11(W10 ) is the recognition of the condition
tested as true (false) with its actual truth; W01 (W00 ) the recognition of the condition
tested as true (false) with its actual falsity. Fuzzy EQR indices, for instance, for
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~
~
~
working operation A : B( A),T ( A) and V ( A) have the membership function
~ ( B( A)), ~ (T ( A))
and V~ (V ( A)) , correspondingly, where B( A)  [ B( A), B ( A)],
B
T
T ( A)  [T ( A), T ( A)], V ( A)  [V ( A), V ( A)] .
One of the most wide-spread forms of fuzzy
~
~
~
values representation is used, namely, expansion of B( A),T ( A) and V ( A) into  levels:
~
~
~
B ( A) 
 [ B ( A), B ( A)] ; T ( A) 
 [V  ( A), V ( A)] .
 [T  ( A), T ( A)] ; V ( A) 
 [0,1]
 [0,1]
 [0,1]
The set of principal standard functional structures (SFS) M SFS contains 12
structures [2]. Each SFS as an algorithmic structure is a binary relation of control
transfer to the set of operators (SO) and conditions (FC, DC). It is also possible to
specify the i -th SFS and equivalent to this SFUO O as n - local relation
O SFSi (Oi , Oi ,...) , where the equivalent SFU (ESFU) O is called a compound
1
2
operation. The compound operation can be only of WO type. To calculate the ESFU
indices, the previously derived formulas the arguments of which are SFU containing
SFS are used. The separate the MMS functioning process (functional network (FN)) is
rerepresented as a SFS superposition [2]:
Oz  SFS i (Oi , Oi ,..., Oi ) ,
1
2
(2)
k
where SFSi  М SFS , Oi j is a simple or compound operation. The simple operation
(the final one) does not have an equivalent SFS, and the compound one is specified by
analogy with (2) – Oi  SFS s (Os , Os ,..., Os ) , SFS s  М SFS , where the operations
j
Os1 , Os2 ,..., Osk
1
2
k
, in its turn, are either simple or compound. Let us say that the two
operations with the same function: F - O( F , E1, Q1 ) and O( F , E2 , Q2 ) are alternative
(“parametric”) ways of fulfilling operations O , as well as OТФСs ( Os1 , Os2 ,...) , i  s
are “structural" ones. The sources of forming parametric alternatives SFU and FN
are, on the whole, alternative values of simple elements parameters (MMS element
structure objects); alternative relations for composite elements; alternative
assignments of elements to simple operations. The alternatives set can be specified
graphically by means of alternative graph (AG) [2]. The generation algorithm
(calculation of EQR) of FN Oz in (2) starts with the most embedded compound
operations Ok ТФСs ( Os1 , Os2 ,...) and extends to the top level Oz ТФСi ( Oi1 , Oi2 ,...) . In
structured programming, three strategies of program development are singled out.
These are bottom-up, top-down and mixed ones. Since the generalized-structured
method [1], lying in the basis of AG, to a significant degree relies on analogical to the
structured programming paradigms, namely SFU, SFS, the “convolution” of SFS to
the equivalent to them SFI, FN analysis and synthesis, then when AG is being formed,
all the three above mentioned strategies can be applied. Let us note the disadvantages
of the structured strategy. As a result of bottom-up and top-down design procedures,
only one invariant form of MA assignment M ( Az )  M inv ( Az ) is generated; duplication
of element structure description with the assignments of MMS similar elements to
different operations; tight binding of implementation techniques to the specific
fragments; difficulties connected with the organization of situation control of the FN
alternatives set structure; weak standardization of FN fragments. The object-oriented
model of description and quantitative estimates of MMS FP indices (object-oriented
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functional network) is constructed by way of synthesis of functional-structured
theory, object-oriented design, fuzzy sets and methods (models) of artificial
intelligence [2]. The basis of this model is the object-oriented method of FP
specifying, the elements of which are classes, objects, relations (of inheritance, filling,
metaclass, application), properties, methods, etc.. Within the framework of this
technique, the description of the set of alternatives and its modification methods is
made. In [2], one-to-one correspondence between the description of MMS FP
alternatives sets for the FN models (functional-semantic models (FSM)) and
production-logical knowledge base in the form of the Prolog language is defined. In
[2], a Prolog-program generating AS taking into account the feasible of variants
implementing the generation algorithm is presented.
IV. THE SEQUENTIAL OPTIMIZATION METHOD
Chapter 3 presents the research results of probability and fuzzy MMS indices in order
to reveal the monotone recursiveness properties. The above properties are further
applied to constructing optimization algorithms.
Chapter 4 considers the method of MMS FP sequential optimization for the functional
net work model within the general scheme of sequential variant analysis method. The
necessary and sufficient condition of optimality and feasibility of partial solutions are
formulated and proved, the estimates of power and labour requirements for generation
of a set of non-dominating alternatives are obtained, the efficiency of various schemes
for approximated optimization algorithms is investigated.
Chapter 5 describes the choice of optimal algorithm for directed exhaustive search by
way of solution to a problem of the given algorithm labour requirements
minimization. A method of solution to the above problem (strategy) related to the
invariant transformation of the alternatives sets: change in the partial solutions
generation sequence, simplification of the necessary optimality conditions for the
particular case of the sets of alternatives and limitations, cancellation of certain check
on the necessary optimality conditions are proposed and theoretically substantiated.
The problem of parallelizing the algorithm for directed exhaustive search consisting
in the solution of the initial optimization problem on several computers is considered.
The structure of the Prolog-program implementing the developed method of
sequential MMS FP optimization directly on the production-logical knowledge base
by way of the inference procedure is described.
In [2], a sequential optimization method for the MMS FP on the basis of SF
model within the framework of general scheme of variants’ sequential analysis
method with the stepwise construction of partial solutions has been developed. A
specific algorithm of stepwise construction is determined by the choice rule of partial
solutions (subnets)  , subject to development at each step, and a test kit  , carrying
out the sifting of those which can’t be completed to the optimal ones. Variation of
parameters  and  leads to various algorithms of the sequential variants analysis
method applied to the MMS FP optimization problems for the functional net works.
The rules of sifting the unpromising partial solutions  are based on the property of
monotone recursiveness of probable and fuzzy indices and depend on the type of
problem (1). The estimation of non-dominated (by Pareto) alternatives power (partial
solutions) is made for the particular case of truncated (without optimal alternative
choice) algorithm for directed search (ADS). The working time is interpreted as mean
time (the number of machine operations) required for the optimization problem
solution. As a result of numerical modeling, the ADS working time estimate has been
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obtained. Also, the working time estimate for verifying the necessary conditions of
partial solutions feasibility as well as the necessary conditions of optimality according
to the efficiency function has been derived. In [3] the description and results of
comparative analysis of approximate methods efficiency for the problem solution (1) :
a sequential genetic algorithm and scheme with additional compression of partial
solutions in ADS, where the advantage of the latter according to accuracy and
deriving the solution is shown, is presented. In [3] the problem of choosing the
optimal ADS as a problem of the given algorithm working time minimization is
stated. Methods for solution to the problem indicated (strategy) connected with the
invariant transformations of the set of alternatives (alternative graph) [2]: changing
the partial solutions generation sequence, simplification of the necessary optimality
conditions (NOC) for the SA partial cases and constraints, cancellation of some
verifications of the NOC themselves are suggested and theoretically substantiated.
The ADS paralleling problem is considered, which consists in solving the initial
optimization problems on several computers in case when it is impossible to obtain
the solution on one computer during the feasible time. The variant selection criterion
of computers distribution among operators of generation and “sifting” partial
solutions with the availability of spare computers the meaning of which consists in the
maximal use of spare (available) computers has been introduced. On the basis of this
criterion, a general scheme for parallel ADS implementation has been suggested. The
Prolog-program structure implementing the method of MMS FP sequential
optimization including ADS optimization strategy directly with the production-logical
knowledge base by means of the inference mechanism is described [2].
V. MMS FP DESIGN TECHNOLOGY
Chapter 6 considers the MMS FP design technologies and software. Elements of
structural and object-oriented approach as well as detailed description of hybrid
expert design system MMS FP INTELLECT-2 are given.
Chapter 7 reviews typical examples of practical application of the developed software
for the MMS FP optimal design problems.
In [2] a conception, the major principles and elements of the MMS functioning
processes design technology according to the EQR probable and fuzzy indices have
been formulated. The basis of the technology is an object-oriented and structural
approach to the MMS FP design, the sequential optimization method and productionlogical knowledge base covering all aspects of the design environment. The design
technology indicated has been implemented most completely in the form of hybrid
expert system INTELLECT-2 functioning on the IBM PC-type computer in the
operational environment Win32, programming languages C++ Builder and Visual
Prolog and offering the user the following opportunities (Fig 1): to specify MMS FP
sets of alternatives the form of alternative graph with the application of structural and
(or) object-oriented technologies; form directories of MMS elements, functions and
SFU used in an object-oriented form; to turn on the arbitrary production-logical
knowledge base in the form of Prolog-program and translate the optimization model
as well as any of its components in the Prolog-program; to determine the optimality
criterions and constraints of the optimization problems on the basis of probable or
fuzzy indices; to make the estimation of power and working time of obtaining the
efficient solutions for all the SFU of the alternative graph; to choose the optimal
algorithm of directed search; to specify the control parameters for the optimization
algorithm; to control the process of optimization problem solution; to select the set of
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effective solutions to the arbitrary SF in AG; to represent the design results and then
store them in the archived file.
Fig. 1. Hybrid expert system INTELLECT-2.
CONCLUSIONS
The models and methods of the MMS FP optimal design considered in the present
monograph do not completely meet the needs of the MMS designers.
The authors think that the long-term problems for further investigation which could
become the topics of dissertation research are as follows:
1. Integration of factor and process MMS optimization models.
2. Developing joint-use technologies for simulation and optimization models.
3. Formulation of optimization problems with the application of linguistic
variables (terms).
4. Taking into account the figures of merit and types of defects in the MMS FP
models when accomplishing an operations.
5. Developing parallel schemes for optimization algorithms.
REFERENCES
Gubinsky A.I., Reliability and Quality of Ergatic Systems Functioning –
Leningrad: Nauka, 1982. (In Russian)
[2] Grif M.G., Tsoi Ye.B., Implementation of the Method of Sequential Variant
Analysis with Complex Systems Optimization according to Fuzzy and Probable
Indices //Siberian Journal of Industrial Mathematics, 2001, Volume IV. No №
2(8). PP. 123-141. (In Russian)
[3] Grif M.G., The Choice of Effective Algorithm of Sequential Man-Machine
Systems Optimization //Papers of Siberian Division of Higher School Academy
of Sciences, № 2 (4). PP. 53-59. (In Russain)
[4] Grif M.G., Tsoi Ye.B. Automation of Designing of Functioning Processes of ManMachine Systems based on the Method of Sequential Optimization. –
Novosibirsk, NGTU: Publishing house , 2005. - 262 p. (In Russian)
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