IMECE2006-13556 AN EXPERIMENTAL STUDY ON VOIDS IN MIXED ALLOY ASSEMBLIES

ABSTRACT The electronics manufacturing industry is gradually migrating towards to a lead-free environment. During this transition, there will be a period where lead-free materials will need to coexist with those containing lead on the same assembly. The use of tin-lead solder with lead-free parts and lead-free solder with components containing lead can hardly be avoided. If it can be shown that lead-free Ball Grid Arrays (BGAs) can be successfully assembled with tin-lead solder while concurrently obtaining more than adequate solder joint reliability, then the Original Equipment Manufacturers (OEMs) will accept lead-free components regardless of the attachment process or material used. Consequently, the Electronics Manufacturing Service (EMS) providers need not carry both the leaded and the unleaded version of a component. Solder voids are the holes and recesses that occur in the joints. Some say the presence of voids is expected to affect the mechanical properties of a joint and reduce strength, ductility, creep, and fatigue life. Some believe that it may slow down crack propagation by forcing a re-initiation of the crack. Consequently, it has the ability to stop a crack. The primary objective of this research effort is to develop a robust process for mixed alloy assemblies such that the occurrence of voids is minimized. Since there is no recipe currently available for mixed alloy assemblies, this research will study and 'optimize' each assembly process step. The difference between the melting points of lead-free (217ºC) and tin-lead (183ºC) solder alloys is the most important constraint in a mixed alloy assembly. The effect of voids on solder joint reliability in tin-lead assembly is well documented. However, its effect on lead-free and mixed alloy assemblies has not received due attention. The secondary objective of this endeavor is to determine the percentage of voids observed in mixed alloy assemblies and compare the results to both tinlead and lead-free assemblies. The effect of surface finish, solder volume, reflow profile parameters, and component pitch on the formation of voids is studied across different assemblies. A designed experiments approach is followed to develop a robust process window for mixed alloy assemblies. Reliability studies are also conducted to understand the effect of voids on solder joint failures when subjected to accelerated testing conditions

Branch and Price Solution Approach for Order Acceptance and Capacity Planning in Make-to-Order Operations

The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver. The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation

A methodology for dynamic planning of road service during a snow fall

Includes bibliographical references (pages [109]-111)Snow and ice-covered roads cause inconvenience to the public, reduce vehicle mobility, and increase the potential for accidents. The regions which experience snow and ice storms require special attention to keep the roads safe for driving and reduce damage to property and personal loss. Any improvement made in the planning o f snow removal can save money to tax payers and the local government. In this research, a generic framework is proposed for the dynamic planning o f the snow removal process. The framework contains a heuristic, a continuous simulation model, and an interface for integrating these two. The framework accommodates both salt spraying and snow plowing operations o f the snow removal process. The framework also considers changes in the snow-fall rate and dynamically determines new routing plans for the snow removal trucks to follow, whenever changes in the snow-fall rate require a new routing plan. The heuristic developed for the framework treats snow removal routes as an undirected, hierarchical network and determines the routing plans for the snow removal trucks. The developed heuristic has been found to give a better solution compared to an existing heuristic, when the subnetwork induced by each hierarchy level is disconnected. The heuristic has also been modified to obtain a lower bound for the Hierarchical Postman Problem applied to the snow removal process. The heuristic has been implemented in Turbo C and validated using thirty-one sample networks. The simulation model developed for the framework is a continuous one, and it considers the changes in the snow-fall rate for dynamically planning the snow removal / process. When executed, the simulation model obtains a routing plan by calling the developed heuristic and simulates the salt spraying and snow plowing operations. When the snow-fall rate changes, the simulation model dynamically revises the snow removal process by calling the heuristic and obtaining a new plan. The simulation model has been implemented using the simulation language SIMAN and has been interfaced with the heuristic using WATCOM C/C++. The implemented framework has been validated using an actual snow removal problem from the city of DeKalb, Illinois. The simulation results have been found to compare favorably with manual computations, thus validating the framework. The details o f the framework, including the developed heuristic and the continuous simulation model, are discussed in this thesis.M.S. (Master of Science

Lower Bounds For Hierarchical Chinese Postman Problem

Arc routing problems aim at finding a least cost traversal on a network with or without additional constraints. The Hierarchical Chinese Postman Problem (HCPP) is an arc routing problem. HCPP is NP-hard and several heuristics have been developed to solve this problem. The Chinese Postman Problem (CPP) tour solution is a known lower bound for the HCPP. This paper presents a heuristic that will prescribe improved lower bounds for the HCPP when compared to the CPP solutions. Better lower bounds aid exact search methods, such as branch-and-bound, to find an optimal solution in a shorter run time. It can also be used to determine the quality of a heuristic solution. Several problem instances were generated to evaluate the proposed heuristic. Experimental results indicate that our lower bounds are better than the CPP solution for all the sample problems chosen

Analytical approximations to predict performance measures of markovian type manufacturing systems with job failures and parallel processing

Manufacturing or service systems with multiple product classes, job circulation due to random failures, resources shared between product classes, and some portions of the manufacturing or assembly carried in series and the rest in parallel are commonly observed in real-life. The web server assembly is one such manufacturing system which exhibits the above characteristics. Predicting the performance measures of these manufacturing systems is not an easy task. The primary objective of this research was to propose analytical approximations to predict the flow times of the manufacturing systems, with the above characteristics, and evaluate its accuracy. The manufacturing system is represented as a network of queues. The parametric decomposition approach is used to develop analytical approximations for a system with arrival and service rates from a Markovian distribution. The results from the analytical approximations are compared to simulation models. In order to bridge the gap in error, correction terms were developed through regression modeling. The experimental study conducted indicates that the analytical approximations along with the correction terms can serve as a good estimate for the flow times of the manufacturing systems with the above characteristics.Queuing network Parametric decomposition Web server assembly Fork and join queues

Performance characterization of complex manufacturing systems with general distributions and job failures

In optoelectronics assembly, the first few stages of the assembly line are dedicated to build the product and the later stages are dedicated for calibration and testing. The assembly line is arranged in a flow shop environment with multiple processors at each stage. When a product (or job) fails at a stage, it is routed back to one of the previous stages or to the same stage (depending upon the nature of the failure). Consequently, the product could circulate between the current stage and the previous stage(s) before it is transferred to the next stage. Estimating the performance measures of such complex manufacturing systems, while considering multiple product classes, random job failures, and resource sharing, is not trivial. This paper presents the approximations used to estimate the performance measures of such complex manufacturing systems with general arrival and service distributions. The analytical approximations have been validated using discrete event simulation and the source of error between them is identified. These approximations can be used by operations managers to estimate the performance measures such as WIP and flow time.Manufacturing Queuing Optoelectronics assembly

Makespan minimization on a single batch processing machine

A batch processing machine (BPM) can process several jobs simultaneously as a batch as long as its capacity is not violated

MAKESPAN MINIMIZATION ON A SINGLE BATCH PROCESSING MACHINE WITH UNEQUAL JOB READY TIMES

A batch processing machine (BPM) can process several jobs simultaneously as a batch as long as its capacity is not violated. The processing time of each job, their ready times and sizes are given. This research was motivated by a practical application observed at an electronics manufacturing facility where a BPM is a bottleneck and consequently minimizing the makespan is the primary objective. The batch processing time is the largest processing time among the jobs in the batch, and the batch ready time is the largest ready time among the jobs in the batch. Given that the problem is NP-hard we propose a constructive heuristic to solve the problem under the assumptions of non-identical job sizes and non-zero job ready times. The computational experiments conducted on a set of randomly generated problem instances show that the proposed approach outperforms other approaches available in the literature at a reasonable computational cost