Filtering by
- All Subjects: Supply Chain Management
- Creators: Wiedmer, Robert
Manufacturing anomalies, inaccurate forecasts, and other problems can lead to SC disruptions. Traditional monitoring methods are not sufficient in this respect, because com- plex SCs feature changes in manufacturing tasks (dynamic complexity) and carry a large number of stock keeping units (detail complexity). Problems are easily confounded with normal system variations.
Motivated by these real challenges faced by modern SC, new surveillance solutions are proposed to detect system deviations that could lead to disruptions in a complex SC. To address supply-side deviations, the fitness of different statistics that can be extracted from the enterprise resource planning system is evaluated. A monitoring strategy is first proposed for SCs featuring high levels of dynamic complexity. This presents an opportunity for monitoring methods to be applied in a new, rich domain of SC management. Then a monitoring strategy, called Heat Map Contrasts (HMC), which converts monitoring into a series of classification problems, is used to monitor SCs with both high levels of dynamic and detail complexities. Data from a semiconductor SC simulator are used to compare the methods with other alternatives under various failure cases, and the results illustrate the viability of our methods.
To address demand-side deviations, a new method of quantifying forecast uncer- tainties using the progression of forecast updates is presented. It is illustrated that a rich amount of information is available in rolling horizon forecasts. Two proactive indicators of future forecast errors are extracted from the forecast stream. This quantitative method re- quires no knowledge of the forecasting model itself and has shown promising results when applied to two datasets consisting of real forecast updates.
The Russian invasion of Ukraine began in February 2022, and has caused a ripple effect of global supply disruptions. The United States, Canada, EU and other allies have responded to the Russian invasion of Ukraine by sanctioning imports from Russia in an attempt to isolate their economy. However, some countries that have not placed trade sanctions on Russia are taking advantage of the opportunity to import from Russia. By integrating import data from Panjiva into a geospatial mapping tool, ArcGIS, global trade patterns can be visualized to understand how global trade is impacted, the effectiveness of Western sanctions on Russia, and potential substitution effects on trade flows from one country to another. First, six key commodities and three countries were identified based on preliminary data analysis. After further analysis, it can be concluded that the Russian sanctions were not effective at isolating their economy for two reasons: certain commodities are critical to our modern lifestyles and some countries took advantage of Western trade sanctions on Russia and increased global trade. In an attempt to diversify their supply, many firms sourced from countries other than Russia, but oftentimes commodities are still sourced from Russia. Lack of supply chain visibility prevents business leaders from making the most efficient supply networks that are in alignment with government regulations.