Personnel selection is a process that takes place in a company in order to have better business performance and competitive advantage. Nowadays, companies have realized the importance of human capital as a necessity for survival in today’s competitive market. There are several methods for selecting staff, but this paper seeks to demonstrate that this selection can be done with the help of an expert system. Metallurgical companies face even greater challenges for managing personnel selection. This research will discover and test the key elements of management personnel selection and implementation of an expert system

I. Iancu

T. Colomeischi

T. Socaciu

English

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Selection of human capital in metallurgical companies using information technology (IT)

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557METALURGIJA 52 (2013) 4, 557-560E. IANCU, T. SOCACIU, T. COLOMEISCHISELECTION OF HUMAN CAPITAL IN METALLURGICAL COMPANIES USING INFORMATION TECHNOLOGY (IT) Received – Prispjelo: 2012-12-08Accepted – Prihvaćeno: 2013-03-30Review paper – Pregledni radISSN 0543-5846METABK 52(4) 557-560 (2013)UDC – UDK 669:061.5:338.91=111E. Iancu, T. Socaciu, T. Colomeischi, Stefan cel Mare University, Faculty of Economics and Public Administration, Suceava, RomaniaPersonnel selection is a process that takes place in a company in order to have better business performance and competitive advantage. Nowadays, companies have realized the importance of human capital as a necessity for survival in today’s competitive market. There are several methods for selecting staff , but this paper seeks to demon-strate that this selection can be done with the help of an expert system. Metallurgical companies face even greater challenges for managing personnel selection. This research will discover and test the key elements of management personnel selection and implementation of an expert system. Key words: metallurgical companies, capital, knowledge, database, algorithmINTRODUCTION During both prosperity and recession period as well, companies seek to realize maximum income by apply-ing a policy resulting from the optimization of processes by increasing effi ciency and economic changes [1]. This can be achieved through a rigorous selection of person-nel serving company.What determines the success of a company is the value generating process in which organizations gener-ate value from their intellectual assets and knowledge [2]. To convert information into knowledge and knowl-edge into information a company needs human resourc-es to generate models, norms, rules [3]. In a company specialist such as technological, economists, lawyers, sociologists help develop the company [4].The notion of artifi cial intelligence gradually emerged and developed, driven by the growing variety of problems in society, diversifi cation of general needs, the ability to transform data into information and infor-mation into knowledge. Artifi cial intelligence provides new dimensions in automation concept, assuming great-er autonomy of production systems, machinery, differ-ent robots [5].Today, expert systems are used in various industries, design and implementation of each type of expert sys-tems (ES) requiring a separate effort and closely con-nected to the type of problem to be solved. Typically, problems for which expert systems are designed and de-veloped must be suffi ciently complex (whether in medi-cine, economics, etc.) to be associated with a database derived from human expertise; solely from such knowl-edge base it becomes effective designing inference en-gine. [6-9].Murphy has shown that the use of expert systems has an adverse effect on the development of subject’s seman-tic memory (declarative knowledge). Therefore, expert systems could function as viable training aid but should not be used as substitutes for actual instruction [10].Without emphasizing historical perspective on the ES, we must consider that P. Harmon and D. King pre-dicted in the 80s two distinct stages of development [11]:  fi rst period until the early 90s, characterized by medi-um-sized application of expert systems to solve spe-cifi c problems, narrowly defi ned on different sec-tors;  second period, expected to be between 1990 and 2000 would be marked by a major focus on quality afford-ed by the ES built, meaning that they were getting closer to the human reasoning.The idea of  using rule-based methods was fi rst pro-posed by Post [12] and the approach is used in grammar specifi cation and construction of grammatical analysis for specifi c programming languages.Finally, we conclude that a period of nearly six dec-ades of theoretical developments and practical applica-tions of ES specifi c results have been obtained in this fi eld of AI, namely:-  costs of constructing ES on areas such as medicine, economics, geology or biology were reduced; current generations of SE are undoubtedly much cheaper than the previous ones;-  although achieved at lower costs, ES came gradually to provide better solutions (although the complexity of the issues for which it was designed increased);-  more extensive use of computer networks – Internet connected naturally with the use of ES in different or-ganizations; work routine and complex iterations once made  by skilled workers were transferred to ES duty.558  METALURGIJA 52 (2013) 4, 557-560E. IANCU et al.: SELECTION OF HUMAN CAPITAL IN METALLURGICAL COMPANIES USING INFORMATION...To describe the basic concept of an expert system, Giarratano Riley identifi es three components: the user providing facts and information to the expert system, basic knowledge containing specifi c information and interference engine that uses rules [13].PROBLEM DEFINITIONPersonnel selection is an area in which ES can pro-vide elements for easy and objective development of the process. Frequently, in company personnel selection takes place in two stages: the fi rst stage is intended to application tests and the second allocated to interview candidates. In the fi rst stage, since the implementation of evaluation tests is a problem, the ES can facilitate the evaluation process. The idea is that tests can be built on four areas frequently used - knowledge, intelligence, skills and personality - with the help of software to ex-tract the test items1 from items fi les created for each of the four areas.The general module includes the following steps [14]1:a) defi ning (M) sets generated by items: - knowledge (C) { } with i=1,2,....NC CiM - intelligence (Q) { } with i=1,2,....NQ QiM - skills (A) { } with i=1,2,....NA AiM- personality (P) { } with i=1,2,....NP PiM where NC, NQ, NA, NP are the maximum numbers of items from each set (MC, MQ, MA, MP)b) for each item it will be defi ned a number of reduc-tions (R) such as: -  knowledge{ },  with i=1,2,....N ; 1,2,...,C C Ci jR j S= -  intelligence{ },  with i=1,2,....N ; 1,2,...,Q Q Qi jR j S= -  skills{ },  with i=1,2,....N ; 1,2,...,A A Ai jR j S= -  personality{ },  with i=1,2,....N ; 1,2,...,P P Pi jR j S= where SC, SQ, SA, SP are the maximum numbers of reductionsc) defi ning collectivities of selection (m) from each area:-  knowledge{ } with i=1,2,....n ;C C C Cim n N≤-  intelligence{ } with i=1,2,....n ;Q Q Q Qim n N≤1 Item - element of a test, survey with a specifi c note in a problem refer-ring to a fragment of its unique and strict determination-  skills{ } with i=1,2,....n ;A A A Aim n N≤-  personality{ } with i=1,2,....n ;P P P Pim n N≤ where nC, nQ, nA, nP are the maximum numbers of items with the reductions afferent to the items:-  knowledge{ },  with i=1,2,....n ; 1,2,...,C C Ci jr j S=-  intelligence{ },  with i=1,2,....n ; 1,2,...,Q Q Qi jr j S=-  skills{ },  with i=1,2,....n ; 1,2,...,A A Ai jr j S=-  personality{ },  with i=1,2,....n ; 1,2,...,P P Pi jr j S= where SC, SQ, SA, SP are the maximum numbers of reductionsd) building general test (T) {T} made of selection sets { }1 2 3 4, , , C Q A Pt t t tm m m m  with the reductions { }1, 1 1, 1 1, 1 1, 1, , , C Q A Pt j t j t j t jr r r r , where:t1= 1,2,...,nC ; j1=1,2,...,SCt2=(nC+1),(nC+2),...(nC+nQ)j2=1,2,...SQt3=(nC+nQ+1),(nC+ nQ +2),...(nC+nQ+nA)j3=1,2,...SAt4=(nC+nQ+nA+1),(nC+ nQ + nA+2),... (nC+nQ+nA+nP)j4=1,2,...SPe) conducting surveys for a number of candidates (K):-  building the vectors with the correct answers( ), t=1,2,...(n + n n n )C Q A PU t + +-  building the matrix with the candidates’ answers:( , ), t=1,2,...(n + n n n ); k=1,2,...KC Q A PW t k + +-  calculating the score for each candidate1 for W(t,k)=U(t)( , )0 for W(t,k) U(t)Z t k =  ≠-  calculating the total score of the candidates:(n + n n n )1Z (n + n n n ) 1, ( , )C Q A PC Q A Ptk Z t k+ += + + + =  ∑The schematic diagram is shown in Figure 1, The system may be a component of an expert system that has attached a module for personnel selection.Procedural components are:- creating fi les with items and reductions;- creating surveys;- applying surveys for a number of candidates-  calculating scores and descending sorting of the candidates.The search algorithm used by the expert system that includes (Search Procedure) is preceded by an ascend-ing sort of rules depending on the complexity of the rules (usually the most complex is the one with the greatest number of facts in the premise), then confl icts are resolved; the situation is as follows: [15]559METALURGIJA 52 (2013) 4, 557-560E. IANCU et al.: SELECTION OF HUMAN CAPITAL IN METALLURGICAL COMPANIES USING INFORMATION...b) relating to formulating and handling expressions:Figure 1  Model of personnel selection expert system in a company [15]In the sequence below, we make a description of how the problem is being raised in making formulas and the possibilities of working with formulas (create, add, change, delete); illustrating a sample is given solely for the purpose of argument:a) relating to the calculation formulas:c)  algorithm relating to the appeal of determining mini-mum and maximum functions:RESULTS The innovations introduced by the expert system to other expert systems in which decision makers do ap-peal in companies are:- designing expert system architecture using a special module that contains data on four different areas: knowledge, intelligence, skills and personality;- realizing a comparative analysis of the results gener-ated by applying an expert system- describing representation methods for various types of data:- descriptive data;- experimental data grouped in different forms for the models used by the expert system;- allows „dynamic” calculations according to the us-er’s/expert’s requirements through the generator module- modularization and generalization of the types of problems with a specially built model; generating expressions and formulas that will be used by the inference engine to defi ne production rules;- facilitates other processing taking into account pos-sibilities for human expert to develop related appli-cations;560  METALURGIJA 52 (2013) 4, 557-560E. IANCU et al.: SELECTION OF HUMAN CAPITAL IN METALLURGICAL COMPANIES USING INFORMATION...- enables exporting the results into Excel fi les which offer graphic and printing facilities;- displaying or printing of the results/conclusions of the expert system for the company which selects staff.CONCLUSIONSThis paper has showed the main factors infl uencing the selection of staff in a company and if the selection is more effi cient by using an expert system rather than us-ing human factor in decision making. Due to this objec-tive, large metallurgical companies may employ per-sonnel when using modules of items that consider knowledge, intelligence, skills and personality. The re-search shows that organizational infrastructure and IT culture are signifi cant in implementing knowledge man-agement. So, metallurgical companies should consider these factors and try to improve organizational culture in terms of KM and IT infrastructure, which has a large impact on all aspects of organization.REFERENCES[1]  K. Grzybowska, B. Gajdzik - Optymisation of Equipment Setup Processes in Enterprises, Metalurgija 51 (2012) 4, 555-558[2]  Levinson M. - Knowledge management defi nition and so-lutions. [Online] Available: http://www.cio.com/arti-cle/40343/Knowledge_Management_Defi nition_and_So-lutions,(2003) [3]  Nickols F. - The knowledge management yearbook, Goo-gle books, (2008), 12-13[4]  B. Gajdzik, A. Wyciślik - Assessment of Environmental Aspects in a Metallurgical Enterprise, Metalurgija 51 (2012) 4, 537-540[5]  I. Stanković, M. Perinić, Z. Jurković, V. Mandić, S. 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Addison-We-sley, (1999)[10]  Murphy, D.S - Expert System Use and the Development of Expertise in Auditing: A Preliminary Investigation, The Journal of Information Systems, 4, (1990), 18-35[11]  Harmon P., Maus R., Morrissey W. – Expert Systems Tools and Applications, New York, John Wiley &Sons, Inc., (1988)[12]  Post E. L. - Formal Reductions of the General Combinato-rial Decision Problem, American Journal of Mathematics 65 (1943), 197-215[13]  Giarratano, J.C., Riley, G.D. - Introduction To Expert Sy-stems. Expert Systems 4th Edition. Thomson Course Tech-nology, (2005),(19,29,32,34)[14]  Constantin A. Bob; Mirela Visean; Mihai Fulea; Andreea Saseanu - Sisteme informatice in comert, Editura ASE, Bucuresti, (2003)[15]  E. Iancu – Sisteme expert in contabilitate si informatica de gestiune, Ed. Politehnica, Timisoara, (2011), 114-116Note:  The responsible translator for English language is lecturer N. Gales and E. F.G. Iancu, Faculty of Economics and Public Ad-ministration, Suceava, Romania

Selection of human capital in metallurgical companies using information technology (IT)

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