Krishna K. Krishnan

Design of robust layout for Dynamic Plant Layout Problems

In this paper, a design for robust facility layout is proposed under the dynamic demand environment. The general strategy for a multi period layout planning problem is adaptive approach. This approach for Dynamic Plant Layout Problem (DPLP) assumes that a layout will accommodate changes from time to time with low rearrangement and production interruption costs, and that the machines can be easily relocated. On the other hand the robust layout approach, assumes that rearrangement and production interruption costs are too high and hence, tries to minimize the total material handling costs in all periods using a single layout. Robust approach suggests a single layout for multiple scenarios as well as for multiple periods. As a solution procedure for the proposed model, a Simulated Annealing (SA) algorithm is suggested, which perform well for the problems from literature and QAPLIB website. The application of suggested model for robust layout to cellular layouts has given better results compared to the robust cellular layout model of literature. For the standard DPLP of the literature, the solution values of the suggested model are very near to the results of adaptive approach. The Total Penalty Cost (TPC) is used to test the suitability of the suggested layout to be a robust layout for the given data set. TPC values indicate that the suggested layout is suitable as robust layout for the given data sets.

Facility layout design for multiple production scenarios in a dynamic environment

Facility design approaches often focus on a single production demand scenario and develop a layout that minimises the Material Handling (MH) costs for that scenario. In a volatile and uncertain production environment, facility layouts should be designed while taking into consideration multiple demand scenarios to minimise the effects of uncertainty. In a risk-averse situation, where multiple probable demand scenarios exist, designing the layout for any one scenario could lead to high losses if any other scenario occurs. In such situations, all demand scenarios have to be considered and the facility should be designed to minimise the maximum loss (Minmax approach) due to MH costs in a manufacturing plant by considering all possible scenarios. This paper proposes a new facility layout design model to determine a compromise layout that can minimise the maximum loss in MH cost both for single and multiple periods. The model developed has been further modified to address minimisation of the total expected loss as well. The resulting mathematical models are solved to generate improved layouts using Genetic Algorithm (GA) approach. The proposed models are solved for single-period and multiperiod case studies. Results indicate that the proposed models generate compromise layouts which are efficient in reducing maximum possible loss and as well in minimising the total expected loss.

Mitigation of risk in facility layout design for single and multi-period problems

The most desirable characteristic of a facility layout is its ability to maintain its efficiency over time while coping with the uncertainty in product demand. In the traditional facility layout design method, the facility layout is governed by the flow intensity between departments, which is the product flow quantity between departments. Hence, an error in the product demand assessment can render the layout inefficient with respect to material handling costs. Most of the research integrates uncertainty in the form of probability of occurrence of different from-to charts. In an environment where the variability of each product demand is independent, the derivation of ‘probabilistic from-to chart’ based scenario cannot be used to address uncertainty of individual demands. This paper presents an FLP (facility layout problem) approach to deal with the uncertainty of each product demand in the design of a facility layout. Two procedures are presented: the first procedure is utilised to assess the risk associated with the layout, while the second procedure is used to develop the layout that minimises the risk. Results from case studies have shown that the procedure produces a reduction of risk as high as 68%.

A conceptual framework for agent‐based agile manufacturing cells

Abstract.  Agile manufacturing techniques are perceived as the manufacturing systems of the future. Agile manufacturing cells are dynamic and reconfigurable and the modelling of the manufacturing cells and its interaction mechanism is critical to its successful use. This paper deals with the architecture and cooperation mechanism of web‐based agile manufacturing cells. Based on an analysis of structure and organization requirements of agile manufacturing cells and a comparison of three basic architectures of manufacturing systems, the quasi‐heterarchical architecture is used for the agile manufacturing cell. Functional layers are defined in this architecture to make the cells control system reconfigurable and reusable. Agent technology is adopted for implementation of each layers functions to establish an agent‐based model of agile manufacturing cells. Four types of agents including cooperation agent, job management agent, resource broker agent, and resource control agent are defined, and their functions discussed. Finally, a real time interaction mechanism of the agents is presented by considering the activities during the agents’ cooperation in an agile manufacturing cell.

Geometry of the minimum zone flatness functional: planar and spatial case

The zone straightness and flatness functional is constructed from the definition of the measure. The geometry of the straightness functional is illustrated in the plane, and in three dimensions, a novel means to visually represent flatness is described using the zone separation body. The zone separation body is a new construction that is uniquely associated with every measurement dataset and can be used to represent the flatness functional visually.

Analysis of damage costs in supply chain systems

In a supply chain system, products get damaged during shipping due to transportation hazards and poor packaging. The most common hazards in transportation include shocks, vibrations, accident, handling, etc. Damage from accidents and handling issues are not completely within the control of packaging. However, proper packaging can prevent most of the damage from shocks and vibration. The loss due to damage at each stage of the supply chain network can be reduced by selecting the appropriate packaging, transportation method and by shipping under assembled or unassembled condition. There is not much literature available in the area of goods damaged during shipping as applied to supply chain systems. A mathematical model which minimises the total costs (damage costs, shipping costs, and packaging costs) has been developed to address the issue of damage costs. The model is implemented in MATLAB. The mathematical models were verified by using total enumeration strategy. Case studies to illustrate and validate the procedure were developed and implemented in MATLAB.

An optimization-based system for adaptive planning in a discrete part manufacturing environment

An optimization-based decision support tool that can be used for adaptive planning in a discrete part manufacturing environment is presented in this paper. In adaptive planning, the process plan is modified based on the status of the manufacturing system to achieve a higher level of success in the production of parts. Modifications to the process plan could be in the form of routing changes, operational tolerance adjustments, or generation of a new process plan. The mathematical model proposed in this paper covers the first two cases. Solution to the mathematical model generates operational tolerances, assigns machines to operations, provides a measure of process plan feasibility, identifies sources of infeasibility, recommends alternative machines, and identifies the required process capabilities to make an infeasible process plan feasible. Experimental results confirm the effectiveness of the proposed model.

Virtual reality mega-case throughout the curriculum

Education will be revolutionized by the use of virtual reality. The Industrial and Manufacturing Engineering Department at Wichita State University along with industrial partners, Boeing, Cessna, Raytheon, Brittain Machine, and Thayer Aerospace, are creating a set of integrated models of an aerospace manufacturing line that can be used in a virtual reality environment to seamlessly analyze different aspects of the system in an effort to improve it. This paper describes the development of integrated virtual models as an aviation mega-case study. Various aspects of these models are used in the majority of courses in our curricula to illustrate for our students the connection between the knowledge and skills they gain in different courses in the analysis of real-world issues.