Pre­dic­tive risk reduc­tion in sup­ply chains

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When goods like semi­con­duc­tors and com­pu­ter chips can’t be deli­ve­red on time and eco­no­mies around the world falter…

The pro­blem

The col­lapse of sup­ply chains has now reached glo­bal pro­por­ti­ons. Whe­ther chips or semi­con­duc­tors, flour or oil, shor­ta­ges are occur­ring ever­y­where, requi­ring decisive coun­ter­mea­su­res. The PAIRS (Pri­vacy-Aware, intel­li­gent and Resi­li­ent Cri­sis Manage­ment) rese­arch pro­ject aims to create trans­pa­rency and intro­duce pre­cau­tio­nary mea­su­res in order to be able to derive tar­ge­ted mea­su­res for anti­ci­pa­tory risk minimization. 

Behind a final sup­ply chain from the sup­plier to the cus­to­mer are nume­rous other sup­ply chains. This means that if just one of these chains col­lap­ses, the ent­ire pro­cess comes to a standstill. The resul­ting sen­si­ti­vity extends from raw mate­rial extrac­tion to mate­rial pro­cu­re­ment and inclu­des all logisti­cal impon­derables (clo­sure of ports, lack of trans­port opti­ons due to staff shor­ta­ges, etc.). Last but not least, social and ethi­cal aspects, e.g. due to child labor in the recy­cling of elec­tro­nic waste or working con­di­ti­ons in the mining of raw mate­ri­als, also play a role and must be taken into account in accordance with the Sup­ply Chain Act.

The solu­tion

In the PAIRS pro­ject, a ser­vice-ori­en­ted, open data infra­st­ruc­ture is being deve­lo­ped to pre­dict the emer­gence and impact of cri­sis situa­tions. The AI hybrid tech­no­logy of PAIRS will incor­po­rate both the initial cri­sis event and the reac­tions of various actors in a cross-domain data space in order to gene­rate tar­ge­ted recom­men­da­ti­ons for action on this basis. 

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Bene­fit from active pro­ject par­ti­ci­pa­tion with many advantages

The joint pro­ject PAIRS is fun­ded as an AI light­house pro­ject wit­hin the frame­work of the “Inno­va­tion Com­pe­ti­tion Arti­fi­cial Intel­li­gence” by the Federal Minis­try of Eco­no­mics and Cli­mate Pro­tec­tion (BMWK).

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