OptimalCore

The Chinese use the words threat and opportunity to describe a crisis. Likewise, it is obvious that many companies face enormous challenges in the current financial environment whereas other companies try to benefit from such turmoil. It is also certain that when things normalize again there will be winners and losers.

Gustavo Gaeta and Stavros Stefanis, a principal and managing director at KPMG LLP’s Business Performance Services Practice respectively, portray how companies and their management teams in particular can recover and advance during such a crisis by connecting finance and operations, and better managing supply and demand risk throughout the supply chain.

In the introductory article of this series, we described the broad scope of factory planning problems. We also presented the key needed abilities and complementary characteristics of heuristic algorithms that are typically used by Advanced Planning Systems (APSs) in order to provide automated solutions to such problems. These abilities and characteristics are summarized in the following graph.

A classic challenge in the management of assembly lines is how to balance the assignment of work so that there are no bottlenecks in the flow. John Bartholdi, Professor at the Georgia Institute of Technology and Donald Eisenstein, Professor at the University of Chicago present the bucket brigades method, a way of organizing workers on an assembly line so that the line balances itself.

The dedicated website contains the detailed description of this simple, yet intuitive approach, the mathematics behind it, examples were it has been applied successfully and a video from one such real life application!

The metals industry faces a number of unique challenges that put significant pressure on its supply chain planning operations. This is particularly relevant as the industry emerges from the recent economic downturn.

The main characteristics of the metals industry are summarized in the left column of the  following diagram; some of them have been relevant for a long time (marked in green) whereas some only became important more recently (marked in cyan). The right column contains the main challenges that the industry faces as a direct consequence of its characteristics.

A challenging task that we often face is how to describe the benefits and challenges arising from the application of optimization to real life problems. Dr Narayan Venkatasubramanyan, a fellow x-i2er and optimization expert, presents his thoughts on this matter in a funny yet very informative way in this series of articles on optimization.

This is the first in a series of postings which challenge the common conception that linear programming solvers are in general not a good fit when dealing with industrial size factory planning processes that typically consider thousands of manufacturing orders and complex multi-step routings. These findings are the result of our five year engagement with such problems in real life business environments. Here, we take a systematic approach in order to analyze the need for using formal optimization, the challenges that arise in this process and the ways to overcome them.

Factory planning is a general term used to describe a variety of problems in various industries. In make-to-stock environments it is used to describe the planning of stock orders typically driven by demand forecasts. In such environments it is usually implied that a single manufacturing site is considered at a time, meaning that if the company operates more than one factory, it deploys an equal number of factory planning solutions. This is because sourcing decisions have already been taken in the more aggregate master planning solution based on long term agreements with suppliers and customers.