Satya S. Chakravorty

A comparative study of line design approaches for serial production systems

Over the past decade two approaches, just‐in‐time (JIT) and theory of constraints (TOC), for designing and operating production lines have developed, each claiming to be the “correct” way. In addition there are still those who maintain that line balanced (whenever possible) is the optimal method. This study uses simulation to compare each of these approaches for designing and operating production lines under various levels of processing time variability, station downtime, and total system inventory. Not surprisingly, the JIT approach appears to work best when system variability is low. The TOC approach works best when system variability is high. This shows that lines designed using TOC principles perform significantly better than JIT lines when inventory is low, and JIT lines perform significantly better than TOC lines as inventory is added to the system. The traditionally balanced line did not perform best under any of the conditions used in this study.

The evolution of manufacturing cells: An action research study

Abstract This study seeks to explain how and why manufacturing cells evolve over time. The purpose is to prevent many of the cellular manufacturing failures reported in industry. We conclude that manufacturing cells go through, somewhat overlapping, evolutionary stages before they begin to perform at the optimal level. It is important to recognize these evolutionary stages because they must be properly managed in order to reap the benefits of cell implementation efforts. In the first stage, both human and technical problems exist; however human problems dominate – requiring conflict management skills to resolve. In the second stage, human problems improve, and technical problems persist, requiring formal problem-solving methods to resolve. Finally, in the third stage, both human and technical problems improve, and cells begin to perform at the optimal level.

Process Improvement: Using Toyota's A3 Reports

In order to drive process improvement, Toyota uses A3 reports as a tool to identify and solve problems. A3 reports are usually written on paper size 11 inches by 17 inches and are enriched with visuals such as pictures, diagrams, and charts to improve communication. To date, the author has found no study explaining how to implement A3 reports in manufacturing operations. The purpose of this exploratory study is to show how A3 reports were implemented in a successful process improvement project in aircraft maintenance and repair operations. In doing so, he shows a systematic approach, improvement event, and the process used to implement and document A3 reports. The duration of an improvement event is generally four weeks and has four distinct phases: 1) preparation and training; 2) process mapping and current state analysis; 3) process mapping and future state analysis; and 4) implementation and ownership. Important for both practitioners and academicians, the author also discusses implications of A3 report implementation and directions for future research.

How problem-solving really works

Over the years, many researchers have proposed theoretical models of problem-solving. These models work a problem in a sequential and rational manner. Through our professional experience and an action research study, we discovered fundamental differences between what these models describe and what actually happens when problems are solved in a real-world setting. Assisting with a process improvement experience in a plastics company, we discovered that when a problem is properly identified, problem-solving generally follows the theoretical models. However, when a problem is difficult to identify, problem-solving proceeds in a cyclical and apparently irrational manner. Cyclical problem-solving increases the average time of problem-solving and production cost. The authors find that the relationships among the problem-solving steps are much more complex than implied in existing literature. Incorporating this new understanding into process improvement training reduced the variability of the problem-solving time from 44 to 21 min.

An evaluation of the DBR control mechanism in a job shop environment

This study is an evaluation of the drum-buffer-rope (DBR) control mechanism compared to the modified infinite loading (MIL) control mechanism in a job shop environment. Although previous research has shown that the MIL mechanism works well in this environment, this study finds that the DBR control mechanism performs significantly better. The performance of the DBR mechanism improves when the shortest processing time (SPT) dispatching rule is used.

Bottleneck management: theory and practice

Advocates of TOC believe that bottleneck resource restricts an operations ability to make money, and the best way to maximise income is to fully exploit the bottleneck resource. Almost all TOC literature focuses on situations where 100% bottleneck utilisation is applied. Based on the implementation experience, the finding is that the optimal level of bottleneck utilisation should be less than 100% and any attempt to increase utilisation beyond the optimal level brings disastrous results for a door manufacturing plant. In order to improve and maintain the performance of the plant effective bottleneck management is critical. The experience provides a deeper understanding of how to design such plants, which could be beneficial for practising managers and academics working with TOC concepts.

Implications of Cell Design Implementation: A Case Study and Analysis

Abstract Using an implementation experience, Hyer et al. [J. Operat. Manage. 17 (1999) 179] developed a model for implementing cell design consisting of strategic, structural, and operational decisions. While their model was applicable in explaining the implementation experience, it failed to include an analysis of the existing system, operator assignment to cells, and management involvement in the implementation process. In complement, our case study examined the model using an implementation experience in a millwork manufacturing operation. We describe how analysis of the existing system and the assignment of operators to cells were performed. We also find that management played an important role in the implementation process.

Do JIT lines perform better than traditionally balanced lines

Over the past decade, JIT approach for designing and operating lines has evolved to compete on time dimensions. Traditionally, the lines designed and operated using line balancing approach are considered optimal. Uses simulation methodology to compare each of these approaches under various levels of system variability and total inventory in the system. Shows that when system variability is low, the JIT line produces lower cycle time at almost all levels of total inventory in the system. However, when system variability is high the balanced line yields lower cycle time, especially at lower levels of inventory in the system.

Testing the accuracy of employee-reported data: An inexpensive alternative approach to traditional methods

Although Information Technology (IT) solutions improve the collection and validation of operational data, Operations Managers must often rely on self-reported data from workers to make decisions. The problem with this data is that they are subject to intentional manipulation, thus reducing their suitability for decision-making. A method of identifying manipulated data, digital analysis, addresses this problem at low cost. In this paper, we demonstrate how one uses this method in real-world companies to validate self-reported data from line workers. The results of our study suggest that digital analysis estimates the accuracy of employee reported data in operations management, within limited contexts. These findings lead to improved operating performance by providing a tool for practitioners to exclude inaccurate information.

Prioritizing Improvement Projects: Benefit & Effort (B&E) Analysis

Recent research indicates that many improvement (lean or Six Sigma) programs fail to yield desired results in companies. One reason these programs fail is because the improvement opportunities or projects are not correctly prioritized. The purpose of this study is to show how to design and implement benefit and effort (B&E) analysis to prioritize improvement projects in production operations. Considering the companys strategic and tactical objectives, factors for benefit and effort were identified. Benefit was calculated with a weighted average of six factors—quality, service, productivity, safety, saving, and environment. Effort was determined with a weighted average of four factors—personnel, duration, investment, and risk. Both B&E were divided into low and high levels, generating four quadrants. All improvement projects were categorized into one of the four quadrants, and a different implementation priority was adopted for each quadrant. Important for practitioners and academicians, the author discusses many implications of implementation of B&E analysis for prioritizing improvement projects. BIOGRAPHY