Spring 2006 Seminar Series

DATE: Thursday, April 27, 2006
LOCATION: E40-298
TIME: 4:15pm
Reception immediately following in the Philip M. Morse Reading Room, E40-106

SPEAKER:
Seyed M. R. Iravani

Associate Professor of Industrial Engineering and Management Sciences

Northwestern University

TITLE
Workforce Agility in Production and Service Operations Systems

ABSTRACT
Most traditional production system design is based on the idea that workers are tied to specific tasks or workstations. This notion has deep roots in philosophies such as standardization of work and division of labor, which were introduced during the industrial revolution. These concepts naturally evolved into rigid production systems, which could not respond adequately to changes in demand. However, to survive in the current intensive global competition, new strategies have evolved that are much more flexible. For example, Toyota introduced the idea of adapting to demand changes through attaining flexibility in the number of workers. This is called Shojinka in Japanese. The main factor in Shojinka is to use agile (cross-trained) workers who have the proper skills to perform different tasks, and therefore they can be in charge of more than one workstation.

 

The difficulty in modeling production systems with agile workers is that we must combine the complications of modeling rigid production systems with the complexity of scheduling the agile workers. The first step in analyzing these complex production systems is to obtain insight by developing models for systems that are smaller yet similar. Theretofore, in the first part of this talk, we focus on the scheduling problem of an agile (fully cross-trained) worker in a serial production system. Then, in the second part we introduce an Index that is capable of measuring the flexibility achieved through workforce agility. We present examples in production systems (e.g. Conwip lines) as well as service operations systems (e.g. Call Centers) and show that our deterministic Index can accurately predict the performance of stochastic production or service systems with agile workforce.