Fragility as a risk factor at highely optimized LEAN enterprises

Rezime: Simulacione metodologije pružaju niz mogućnosti u analizi, upravljanju i kontroli poslovnih sistema. Kontinualni razvoj simulacionih modela i njihova integracija sa modelima za veštačku inteligenciju postaje sve učestalija u industrijskom inženjerstvu i inženjerskom menadžmentu, a sve sa ciljem boljeg upravljanja procesima. U doktorskoj disertaciji sagledan je segment primene vremenski zavisnih simulacionih modela, koji još uvek nisu dovoljno zastupljeni u odnosu na druge metodologije u industrijskom inženjerstvu. Analiza rizika poslovnih sistema u kombinaciji sa dinamičkim simulacijama, predstavljala je glavni cilj izrade doktorske disertacije. Takođe predmet istraživanja bio je usmeren ka razvoju novog alata za analizu rizika kod poslovnih sistema. Analiza fragilnosti sistema pre publikovanja naučnih radova koji čine osnovu doktorske disertacije, nije imala široku primenu izvan finansijskog sektora. Shodno tome bilo je potrebno sagledati mogućnosti adaptacije ove heurističke metodologije za primenu na druge ekonomske entitete, izvan finansijskog sektora. Predmet istraživanja su bili LEAN sistemi, i njihovo dinamičko ponašanje pod uticajem različitih stresora. LEAN poslovni sistemi se često klasifikuju kao visoko optimizovanim i efikasni u svojim operacijama, međutim ovi sistemi mogu pokazati niz strukturalnih nedostataka u reakciji na eksternu i internu volatilnost. Kao predmet doktorske disertacije bilo je kreiranje simulacionih modela koji su u mogućnosti da detektuju fragilnost visoko optimizovanih LEAN sistema. Kreirani su simulacioni modeli, optimizovani za analizu fragilnosti, gde je analizirana fragilnost u okviru zdravstva i sektora komunalnog otpada. Analizirani sistemi se mogu klasifikovati kao LEAN sistemi, koji su kroz sprovedene analize pokazali fragilnost na neželjene nagle promene. Može se zaključiti da kombinovanje simulacionih tehnologija sa heurističkim metodama za analizu rizika može doprineti razvoju oblasti menadžmenta rizikom.Abstract: Simulation methodologies offer a large spectrum of capabilities in analyzing and managing industrial and service-based systems. In order to improve process management, industrial engineering and engineering management are placing an increasing emphasis on the continuous development of simulation models and their integration with artificial intelligence models. The dissertation examines the area of time-dependent simulation model application, which is still understudied in industrial engineering when compared to other approaches. In the doctoral thesis a highly neglected segment of simulation modeling applications was analyzed. Combining dynamic simulations with risk analysis, represents the central goal of the doctoral thesis. Additionally, research initiative of the thesis was focused on the development of new tools for enterprise risk analysis. The fragility risk analysis, prior to the publications that the doctoral thesis is based upon, did not see many applications outside of the financial sector. Consequently, new methods for adapting this heurist methodology for economic entities outside of the financial sector was developed. The subject of research was LEAN systems and their dynamic behavior under the influence of various stressors. LEAN business systems are often classified as highly optimized and efficient in their operations; however, these systems can exhibit a number of structural weaknesses in their reaction to external and internal volatility. As the subject of the doctoral dissertation, the creation of simulation models capable of detecting fragility in highly optimized LEAN systems was undertaken. Simulation models optimized for fragility analysis were created, with fragility being analyzed in the context of the healthcare and municipal waste sectors. The analyzed systems can be classified as LEAN systems, which through the conducted analysis showed fragility in response to unwanted changes. The doctoral dissertation concludes that the combination of simulation technologies with heuristic methods for risk analysis can contribute to the development of the field of risk management