Kripa Shanker

Impact of information sharing and lead time on bullwhip effect and on-hand inventory

This work analyzes a two echelon (warehouse-retailer) serial supply chain to study the impact of information sharing (IS) and lead time on bullwhip effect and on-hand inventory. The customer demand at the retailer is assumed to be an autoregressive (AR(1)) process. Both the echelons use a minimum mean squared error (MMSE) model for forecasting lead time demand (LTD), and follow an adaptive base-stock inventory policy to determine their respective order quantities. For the cases of without IS and inter as well as intra echelon IS, expressions for the bullwhip effect and on-hand inventory for the warehouse are obtained, considering deterministic lead-time. The results are compared with the previous research work and an easy analysis of the various bullwhip effect expressions under different scenarios, is done to understand the impact of IS on the bullwhip effect phenomenon. It is shown that some part of bullwhip effect will always remain even after sharing both inter as well as intra echelon information. Further, with the help of a numerical example it is shown that the lead time reduction is more beneficial in comparison to the sharing of information in terms of reduction in the bullwhip effect phenomenon.

Some solution methodologies for loading problems in a flexible manufacturing system

SUMMARY The loading problem in a flexible manufacturing system (FMS) is viewed as selecting a subset of jobs from the job pool and allocating jobs among machines. A two-stage branch and backtrack procedure is developed with the objective of maximizing the assigned workload. Heuristic procedures are also developed with a bicriterion objective of minimizing the workload imbalance and maximizing the throughput for critical resources such as the number of tool slots on machines and the number of working hours in a scheduling period. The case of machine-dependent processing times is also dealt with. An illustrative numerical example accompanies each procedure.

DETERMINATION OF OPTIMAL AGV FLEET SIZE FOR AN FMS

The required number of AGVs necessary to perform a given level of material handling task in an FMS environment is determined using analytical and simulation modelling. The analytical method involves consideration of load handling time, empty travel time, and waiting and blocking time. Load handling time is computed from given system parameters. Determination of empty vehicle travel is difficult due to the inherent randomness of an FMS. Several research studies for this purpose are discussed and a new model is proposed. It entails formulation of a mixed integer programme with an objective of minimizing empty trips. The constraints are in the form of upper and lower bounds placed on the total number of empty trips starting from or ending at a load transfer station. The phenomena of vehicle waiting and blocking are also discussed. The cumulative impact of these three time estimates are then translated into an initial estimate of AGV fleet size as predicted by individual models. The method is applied to an il...

Grouping of parts and machines in presence of alternative process routes by genetic algorithm

Abstract This paper addresses generalized grouping problem where each part has more than one process routes. The problem of simultaneously assigning machines and process routes (parts) to cells is formulated as an integer-programming problem. The objective of minimization of intercell movements is achieved by minimizing the number of visits to various cells required by a process route for processing the corresponding part. A procedure based on genetic algorithm is suggested as a solution methodology. The working of the proposed algorithm is illustrated with a numerical example and found that it can be a powerful tool for solving grouping problems.

A genetic algorithm for FMS part type selection and machine loading

Part type selection (PTS) and machine loading are two major problems in the production planning of flexible manufacturing systems. In this paper, we solve these problems by the use of genetic algorithms (GAs). We exploit the problems MIP (mixed integer programming) model to make our GA more meaningful and less computation-intensive. The GA strategy is developed in three parts: solution coding, solution generation and solution recombination. In solution coding, we replace the original binary routing variables with integer variables and thus reduce the chromosome length significantly. In solution generation, the level of feasibility is the main concern. We divide the constraints into two categories: direct and indirect. The direct constraints involve only two variables each and are easily satisfied by context-dependent genes. Since the direct constraints form the major chunk of constraints, their satisfaction controls infeasibility to a large extent. The remaining indirect constraints are handled by the penalty function approach. The solution recombination involves crossover and mutation. The crossover is performed in two steps, the PTS swap followed by the routing swap, so that the feasibility level is not disturbed. With a similar intent, the mutation is allowed to operate only on selective genes. All the steps are illustrated with examples. Our GA is able to achieve optimum or near-optimum performance on a variety of objectives. A parametric study of GA factors is also carried out, indicating population size and mutation probability as influential parameters.

Two-echelon supply chain inventory model with controllable lead time and service level constraint

This paper considers a two-echelon supply chain inventory problem consisting of a single-vendor and a single-buyer. In the system under study, a vendor produces a product in a batch production environment and supplies it to a buyer facing a stochastic demand, which is assumed to be normally distributed. Also, buyers lead time is controllable which can be shortened at an added cost and all shortages are backordered. A model has been formulated for an integrated vendor-buyer problem to jointly determine the optimal order quantity, lead time and the number of shipments from the vendor to the buyer during a production cycle while minimizing the total expected cost of the vendor-buyer integrated system. It is often difficult to estimate the shortage cost in inventory systems. Therefore, instead of having a shortage cost term in the objective function, a service level constraint (SLC) is included in the model that requires a certain proportion of demands to be met in each cycle. An efficient procedure has been suggested to find the bounds on number of shipments and then, an algorithm is developed to obtain the optimal solution of the proposed model. A numerical example is included to illustrate the algorithmic procedure and the effects of key parameters are studied to analyze the behavior of the model. Finally, the savings of buyer and vendor are investigated from implementation of joint optimization model over the model in which they minimize their own cost independently.

A semi-dynamic time window constrained routeing strategy in an AGV system

This study addresses the issue of vehicle route planning in an AGV system. The two salient approaches to route planning static and dynamic are briefly discussed. The main thrust of the present work is development and testing of a proposed semi-dynamic time window constrained routeing strategy. Reserved time windows are placed on nodes indicating sequential crossing of nodes by the respective vehicles. Free time windows represent empty time slots available for vehicles to cross the nodes. Similarly, time windows representing the direction of traffic flow are placed on the bidirectional arcs. Based on these time windows, Dijkstras algorithm is applied to find the least congested fastest routes for vehicles. A simulation study of a bidirectional flow path is then reported. The aim of the simulation experiment is to evaluate the system performance under the proposed routeing strategy vis-a-vis static routeing strategy. The results show that the proposed routeing strategy helps in reducing vehicle blocking ti...

A single-vendor single-buyer production-inventory model with controllable lead time and service level constraint for decaying items

This paper presents a production-inventory model in a single-vendor single-buyer system for decaying items which deplete with constant decay rate. It is assumed that the lead time demand follows a normal distribution and shortages are backordered. Also, buyers lead time can be reduced at an added cost. A model has been formulated to find the optimal order quantity, lead time and the number of shipments from the vendor to the buyer during one production cycle while minimising the total expected cost per unit time of the vendor-buyer integrated system. It is often difficult to estimate the stock-out cost in inventory systems. Therefore, instead of having a stock-out term in the objective function, a service level constraint is included in the model. Due to mathematical complexities involved, it is difficult to establish the solutions analytically. An iterative procedure is developed to find the optimal solution using LINGO 10, and a numerical example is given to illustrate the results of the proposed model. Furthermore, the effects of key parameters are also studied to provide the insight into the structure of the solution. In addition, the savings of buyer and vendor are investigated from implementation of joint optimisation model over the model in which they minimise their own cost independently.

A branch and bound based heuristic for multi-product resource constrained scheduling problem in FMS environment

Abstract This paper addresses an inter-dependent multiple-product resource-constrained scheduling problem with the objective of makespan minimization in a flexible manufacturing system with resource flexibility. Both consumable and non-consumable resources are considered along with their alternative types and constrained utilization rates. A 0–1 integer linear programming formulation is presented for the problem. The complexity of the problem is observed to be at increase with the availability of alternate resources for product operations. A branch and bound based heuristic is proposed as a solution methodology. A numerical example is presented to illustrate the problem and the effectiveness of the heuristic.

An heuristic for configuring a mixed uni/bidirectional flow path for an AGV system

An heuristic methodology has been developed in the present work for configuring a mixed (hybrid) uni/bidirectional flow path for an AGV material handling system. The given unidirectional flow path layout, material flow intensities and vehicle travelling time matrix among various processing centres are taken as input information to this technique. A multiplicative function of material flow intensities between any two centres is used as a criterion for selectively configuring a path as a bidirectional one. The highest such product indicates that the shorter path between that pair of centres is a strong candidate for being configured as bidirectional. The heuristic has been applied to an illustrative FMS and various alternate flow path designs have been obtained. Simulation is then performed with the aim of comparing the productive potentials of the facility when it is operated on either unidirectional, or mixed uni/bidirectional, or allbidirectional flow path design alternatives. The benefits of bidirection...