MODELLING SUPPLY CHAIN RESILIENCE

Transcription

1 Università degli MODELLING SUPPLY CHAIN RESILIENCE TERESA MURINO, ELPIDIO ROMANO, LIBERATINA C. C SANTILLO

2 Aims and Purposes It has been noted how many companies better overcome those risks: they share a critical feature: the resilience The modern aim ofbusiness this work world is to is facing providepressures a proposal heavier in than supply ever. chain Therisk catastrophic management events finding of recent key-lever yearsto as Economic adjust resilience recession,the in supply Twin Towers chain. terrorist attack of 11/09, the SARS epidemic, Hurricane Katrina and the Middle East wars have shown how a company is vulnerable to events such as unexpected as catastrophic as well have changed the concept of preparation to disasters.

3 AGENDA Overview of Supply Chain defitions Supply chain risk management and vulnerability causes Avoiding risks: Resilience System Dynamics supply chain model Simulation approach

4 PRODUCTION Supply SYSTEM ChainDESIGN A supply chain is a network of resources that performs the functions of procurement materials, and more generally of the input production, processing of these products in intermediate and finished goods, distribution and delivery finished products to customers, which is composed of independent companies that share the same goal.

5 PRODUCTION SYSTEM DESIGN y SCRM and Vulnerability Supply Chain Risk Management (SCRM) is a discipline of Risk Management which attempts to identify potential disruptions Apart from to continued extemporaneous manufacturing events production such and as thereby commercial financial exposure. Terrorist Attacks, epidemics or earthquakes, there are "Structural" reasons that justify the great relevance of the theme.

6 PRODUCTION Supply Chain SYSTEM Risk DESIGN Category The supply chain risks can be classified in very different ways and by different perspectives. Inside the enterprise, there are a process and a control risk; outside the enterprise but inside the supply chain there can be identified a network risk, divided in demand and supply. Finally, outside the network, there is environmental risk.

7 PRODUCTION Resilience SYSTEM DESIGN Unfortunately it does not exist a safe way to overcome these risks, but some organization overcomes better than others not quantifiable risks and symptoms. They share a critic characteristic: the resilience. In the material science, the resilience is the ability of a material to reacquire its original shape after a deformation, while, in the business sector, resilience refers to the ability of a company to resist to a serious s damaging event.

8 PRODUCTION Strenght vs. SYSTEM Resilience DESIGN A resilient company is able to better support the unpredictability Strong means of the thatglobal it is trade able obtaining to a resist to an unexpected Resilient event means, on the competitive advantage, being able and to come back in the contrary, same able to come back in to make up more quickly than the steady situation a new (often "inferior") steady competitors when happens a A strong system situation with respect to that catastrophe. will maintain A resilient system shall intact its structure subsisting before the event. adapt itself to find a new In a business, steady the capacity position. to survive (resilience) is much more important than the ability to rapidly recover the steadiness (strength).

9 PRODUCTION Resilience SYSTEM in Supply DESIGN Chain At this point the company must prepare to recover itself. The destructive event is preceded by a "warning time" in which the company can (in some cases) predict what is If it is no possible going to happen Resumption to avoid materializes the and act by gradually disruption after a recovery on time, consequence time, it will and manifest bring the itself company in all its to strength a level of performance after a small that is often lower than interval the of one time before due to the a delayed impact. impact.

10 PRODUCTION Building a SYSTEM Resilient DESIGN Supply Chain According to Professor Martin Christopher there are 5 basic principles that allow the creation of amore resilient supply chain According to Prof. Y. Sheffy there are 3 aspects that have a different SC understanding contribution in resilience growth. Supply base strategy SC collaboration Agility Risk management culture Redundancy Flexibility Company culture

11 PRODUCTION pp y SYSTEM DESIGN SD Supply Chain Model To note massive improvements that resilience can bring in a Supply chain, a system dynamical model has been built with ih Powersim Powersim software. A set of data has been used to forecast future customers orders To through represent the the delayed auxiliary sales Demand of products generated planning by previous order, the Orders auxiliary has been linked with another auxiliary named Delayed l d sales that plays its role through a delay function. Future forecast are necessary to calculate the desired level of stock in RM warehouse Desired warehouse represent the raw materials level of stock The model that should starts satisfy from market an exogenous input demand formed by the Orders auxiliary that simulate customer demand through agraph function.

12 PRODUCTION Model Overview SYSTEM DESIGN Max production Orders RM0 WIP0 FP0 Raw material flow Production flow 1 Production flow 2 Shipments Raw materials WIP Finished product Sold products Supply time WIP production time FP production time Safety stock Desired warehouse Desired WIP Future forecasting Future forecasting Safety stock Demand planning Forecasting error average Delayed sales Backlog Datas Gap Orders to suppliers Orders Fulfilled backlog Daily orders not fulfilled

13 PRODUCTION Results SYSTEM DESIGN The simulation yelded the following results 40 euros widgets/da Backlog (wdg) Orders (wdg/da) Shipments (wdg/da) Finished product (wdg) 5 Total costs Total revenues Total profits Production flow st qt 2nd qt 3rd qt 4th qt 1st qt 2nd qt 3rd qt 4th qt Non-commercial use only! Non-commercial use only! 0 1st qt 2nd qt 3rd qt 4th qt Non-commercial use only! Costs, revenues and profits

14 PRODUCTION Model Overview SYSTEM DESIGN Max production Backlog Auxiliary_1 Orders RM0 WIP0 FP0 Raw material flow Production flow 1 Production flow 2 Shipments Raw materials WIP Finished product Sold products Supply time Increase_raw_mate rials WIP production time FP production time Safety stock Desired warehouse Desired WIP Future forecasting Safety stock Future forecasting Flow_production_in crease Demand planning Forecasting error average Delayed sales Backlog Datas Gap Orders to suppliers Orders Fulfilled backlog Daily orders not fulfilled

15 PRODUCTION Perturbation SYSTEM DESIGN It has been analyzed the responses of the model hit by an unexpected demand variation. DEMAND FORECASTED DEMAND

16 PRODUCTION Model Analysis SYSTEM DESIGN The demand variation provides the following results euros Backlog peak Negative profits Daily orders not fulfilled (wdg/da) Total costs Backlog (wdg) Total revenues Fulfilled backlog (wdg/da) Total profits 0 0 1st qt 2nd qt 3rd qt 4th qt 1st qt 2nd qt 3rd qt 4th qt Non-commercial use only! Non-commercial use only!

17 PRODUCTION Results with SYSTEM demand DESIGN perturbation wid g e ts /d a Backlog (wdg) Orders (wdg/da) Shipments (wdg/da) Finished product (wdg) Production flow 1 0 1st qt 2nd qt 3rd qt 4th qt Non-commercial use only! 0 1st qt 2nd qt 3rd qt 4th qt Non-commercial use only! we have implemented an artifact in the model to take account of the disruption, whereby if the backlog grows beyond the capacity can be relied to an increase in the production flow or max production.

18 PRODUCTION Conclusions SYSTEM DESIGN In this work we design a model in SD environment that t reproduce the real behavior of the typical Supply Chain; We simulate the model and will use this to the what if analysis to determine different scenario in the real behavior; Definition a logical modeling analysis to determine a decision support for the different supply network.

19 PRODUCTION Future developments SYSTEM DESIGN This model can be made more robust in order to show its performances even if stressed by different types of disruptions: Calibration analysis. The model can be also upgraded and adapted to various supply chain adding or cutting elements from itself. It can be used to plan maintenance or to analyze system response to unexpected failures or strikes.