PCB assembly line assignment:a genetic algorithm approach

Purpose – This paper sets out to study a production-planning problem for printed circuit board (PCB) assembly. A PCB assembly company may have a number of assembly lines for production of several product types in large volume. Design/methodology/approach – Pure integer linear programming models are formulated for assigning the product types to assembly lines, which is the line assignment problem, with the objective of minimizing the total production cost. In this approach, unrealistic assignment, which was suffered by previous researchers, is avoided by incorporating several constraints into the model. In this paper, a genetic algorithm is developed to solve the line assignment problem. Findings – The procedure of the genetic algorithm to the problem and a numerical example for illustrating the models are provided. It is also proved that the algorithm is effective and efficient in dealing with the problem. Originality/value – This paper studies the line assignment problem arising in a PCB manufacturing company in which the production volume is high.

Component scheduling for chip shooter machines: a hybrid genetic algorithm approach

A chip shooter machine for electronic component assembly has a movable feeder carrier, a movable X–Y table carrying a printed circuit board (PCB), and a rotary turret with multiple assembly heads. This paper presents a hybrid genetic algorithm (HGA) to optimize the sequence of component placements and the arrangement of component types to feeders simultaneously for a chip shooter machine, that is, the component scheduling problem. The objective of the problem is to minimize the total assembly time. The GA developed in the paper hybridizes different search heuristics including the nearest-neighbor heuristic, the 2-opt heuristic, and an iterated swap procedure, which is a new improved heuristic. Compared with the results obtained by other researchers, the performance of the HGA is superior in terms of the assembly time. Scope and purpose When assembling the surface mount components on a PCB, it is necessary to obtain the optimal sequence of component placements and the best arrangement of component types to feeders simultaneously in order to minimize the total assembly time. Since it is very difficult to obtain the optimality, a GA hybridized with several search heuristics is developed. The type of machines being studied is the chip shooter machine. This paper compares the algorithm with a simple GA. It shows that the performance of the algorithm is superior to that of the simple GA in terms of the total assembly time.

A genetic algorithm approach to optimising component placement and retrieval sequence for chip shooter machines

A chip shooter machine in printed circuit board (PCB) assembly has three movable mechanisms: an X-Y table carrying a PCB, a feeder carrier with several feeders holding components and a rotary turret with multiple assembly heads to pick up and place components. In order to get the minimal placement or assembly time for a PCB on the machine, all the components on the board should be placed in a perfect sequence, and the components should be set up on a right feeder, or feeders since two feeders can hold the same type of components, and additionally, the assembly head should retrieve or pick up a component from a right feeder. The entire problem is very complicated, and this paper presents a genetic algorithm approach to tackle it.

A genetic algorithm to optimise the component placement process in the PCB assembly

In printed circuit board (PCB) assembly, the efficiency of the component placement process is dependent on two interrelated issues: the sequence of component placement, that is, the component sequencing problem, and the assignment of component types to feeders of the placement machine, that is, the feeder arrangement problem. In cases where some components with the same type are assigned to more than one feeder, the component retrieval problem should also be considered. Due to their inseparable relationship, a hybrid genetic algorithm is adopted to solve these three problems simultaneously for a type of PCB placement machines called the sequential pick-and-place (PAP) machine in this paper. The objective is to minimise the total distance travelled by the placement head for assembling all components on a PCB. Besides, the algorithm is compared with the methods proposed by other researchers in order to examine its effectiveness and efficiency.

A genetic algorithm for the generalised transportation problem

The generalised transportation problem (GTP) is an extension of the linear Hitchcock transportation problem. However, it does not have the unimodularity property, which means the linear programming solution (like the simplex method) cannot guarantee to be integer. This is a major difference between the GTP and the Hitchcock transportation problem. Although some special algorithms, such as the generalised stepping-stone method, have been developed, but they are based on the linear programming model and the integer solution requirement of the GTP is relaxed. This paper proposes a genetic algorithm (GA) to solve the GTP and a numerical example is presented to show the algorithm and its efficiency.

A hybrid genetic algorithm for sequencing PCB component placement

A chip shooter machine for electronic components assembly has a movable feeder carrier holding components, a movable X-Y table carrying a printed circuit board (PCB), and a rotary turret having multiple assembly heads. This paper presents a hybrid genetic algorithm to optimize the sequence of component placements for a chip shooter machine. The objective of the problem is to minimize the total traveling distance of the X-Y table or the board. The genetic algorithm developed in the paper hybridizes the nearest neighbor heuristic, and an iterated swap procedure, which is a new improved heuristic. We have compared the performance of the hybrid genetic algorithm with that of the approach proposed by other researchers and have demonstrated our algorithm is superior in terms of the distance traveled by the X-Y table or the board.

A hybrid genetic algorithm for component sequencing and feeder arrangement

This paper presents a hybrid genetic algorithm to optimize the sequence of component placements on a printed circuit board and the arrangement of component types to feeders simultaneously for a pick-and-place machine with multiple stationary feeders, a fixed board table and a movable placement head. The objective of the problem is to minimize the total travelling distance, or the travelling time, of the placement head. The genetic algorithm developed in the paper hybrisizes different search heuristics including the nearest neighbor heuristic, the 2-opt heuristic, and an iterated swap procedure, which is a new improving heuristic. Compared with the results obtained by other researchers, the performance of the hybrid genetic algorithm is superior to others in terms of the distance travelled by the placement head.

Design of a genetic algorithm for bi-objective flow shop scheduling problems with re-entrant jobs

This paper presents a simulated genetic algorithm (GA) model of scheduling the flow shop problem with re-entrant jobs. The objective of this research is to minimize the weighted tardiness and makespan. The proposed model considers that the jobs with non-identical due dates are processed on the machines in the same order. Furthermore, the re-entrant jobs are stochastic as only some jobs are required to reenter to the flow shop. The tardiness weight is adjusted once the jobs reenter to the shop. The performance of the proposed GA model is verified by a number of numerical experiments where the data come from the case company. The results show the proposed method has a higher order satisfaction rate than the current industrial practices.

Statistical deconvolution of enthalpic energetic contributions to MHC-peptide binding affinity

Background - MHC Class I molecules present antigenic peptides to cytotoxic T cells, which forms an integral part of the adaptive immune response. Peptides are bound within a groove formed by the MHC heavy chain. Previous approaches to MHC Class I-peptide binding prediction have largely concentrated on the peptide anchor residues located at the P2 and C-terminus positions. Results - A large dataset comprising MHC-peptide structural complexes was created by re-modelling pre-determined x-ray crystallographic structures. Static energetic analysis, following energy minimisation, was performed on the dataset in order to characterise interactions between bound peptides and the MHC Class I molecule, partitioning the interactions within the groove into van der Waals, electrostatic and total non-bonded energy contributions. Conclusion - The QSAR techniques of Genetic Function Approximation (GFA) and Genetic Partial Least Squares (G/PLS) algorithms were used to identify key interactions between the two molecules by comparing the calculated energy values with experimentally-determined BL50 data. Although the peptide termini binding interactions help ensure the stability of the MHC Class I-peptide complex, the central region of the peptide is also important in defining the specificity of the interaction. As thermodynamic studies indicate that peptide association and dissociation may be driven entropically, it may be necessary to incorporate entropic contributions into future calculations.

Multi-level genetic algorithm for the resource-constrained re-entrant scheduling problem in the flow shop

The re-entrant flow shop scheduling problem (RFSP) is regarded as a NP-hard problem and attracted the attention of both researchers and industry. Current approach attempts to minimize the makespan of RFSP without considering the interdependency between the resource constraints and the re-entrant probability. This paper proposed Multi-level genetic algorithm (GA) by including the co-related re-entrant possibility and production mode in multi-level chromosome encoding. Repair operator is incorporated in the Multi-level genetic algorithm so as to revise the infeasible solution by resolving the resource conflict. With the objective of minimizing the makespan, Multi-level genetic algorithm (GA) is proposed and ANOVA is used to fine tune the parameter setting of GA. The experiment shows that the proposed approach is more effective to find the near-optimal schedule than the simulated annealing algorithm for both small-size problem and large-size problem. © 2013 Published by Elsevier Ltd.

Does money matter in inflation forecasting

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. In our forecasting experiment we use two non-linear techniques, namely, recurrent neural networks and kernel recursive least squares regression - techniques that are new to macroeconomics. Recurrent neural networks operate with potentially unbounded input memory, while the kernel regression technique is a finite memory predictor. The two methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a naive random walk model. The best models were non-linear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation.

Satisfaction with knowledge and competencies:a multi-country study of employers and business graduates

This study critically discusses findings from a research project involving four European countries. The project had two main aims. The first was to develop a systematic procedure for assessing the balance between knowledge and competencies acquired in higher, further and vocational education and the specific needs of the labor market. The second aim was to develop and test a set of meta-level quality indicators aimed at evaluating the linkages between education and employment. The project was designed to address the lack of employer input concerning the requirements of business graduates for successful workplace performance and the need for more specific industry-driven feedback to guide administrative heads at universities and personnel at quality assurance agencies in curriculum development and revision. Approach: The project was distinctive in that it combined different partners from higher education, vocational training, industry and quality assurance. Project partners designed and implemented an innovative approach, based on literature review, qualitative interviews and surveys in the four countries, in order to identify and confirm key knowledge and competency requirements. This study presents this step-by-step approach, as well as survey findings from a sample of 900 business graduates and employers. In addition, it introduces two Partial Least Squares (PLS) path models for predicting satisfaction with work performance and satisfaction with business education. Results: Survey findings revealed that employers were not very confident regarding business graduates’ abilities in key knowledge areas and in key generic competencies. In subsequent analysis, these graduate abilities were tested and identified as important predictors of employers’ satisfaction with graduates’ work performance. Conclusion: The industry-driven approach introduced in this study can serve as a guide to assist different types of educational institutions to better align study programs with changing labor market requirements. Recommendations for curriculum improvement are discussed.

Fatty acid composition, antioxidants and lipid oxidation in chicken breasts from different production regimes

Chicken breast from nine products and from the following production regimes: conventional (chilled and frozen), organic and free range, were analysed for fatty acid composition of total lipids, preventative and chain breaking antioxidant contents and lipid oxidation during 5 days of sub-ambient storage following purchase. Total lipids were extracted with an optimal amount of a cold chloroform methanol solvent. Lipid compositions varied, but there were differences between conventional and organic products in their contents of total polyunsaturated fatty acids and n-3 and n-6 fatty acids and n-6:n-3 ratio. Of the antioxidants, a-tocopherol content was inversely correlated with lipid oxidation. The antioxidant enzyme activities of catalase, glutathione peroxidase and glutathione reductase varied between products. Modelling with partial least squares regression showed no overall relationship between total antioxidants and lipid data, but certain individual antioxidants showed a relationship with specific lipid fractions.

Relationships between flavour, lipid composition and antioxidants in organic, free-range and conventional chicken breasts from modelling

Consumers expect organic, free-range and corn-fed chicken to be nutritionally wholesome and have premium flavour characters. Interrelationships between flavour, fatty acids and antioxidants of retailed breasts were explored using simple correlations and chemometrics. Saturated fatty acid C16:0, and n-6 polyunsaturated C20:4 and C22:4 contents were correlated with lipid oxidation products (thiobarbituric acid reactive substances) and in partial least-squares regression (PLS1) with 32 high-resonance gas chromatography (flame ionization) flavour components (r2>0.90), and also linked (r2>0.80) to antioxidants (-tocopherol, glutathione and catalase). A further 10 high-resonance gas chromatography nitrogen phosphorus detector flavour components were correlated (r 2>0.85) with C18:3(n-3) content. Chicken character was correlated with C18:3(n-3), and C18:3(n-6) inversely with oily, off-flavour and lipid oxidation. Sweet, fruity and oily aromas were linked in PLS1 with 13 specific fatty acids (r2>0.6), and bland taste with total summed (six) fatty acid fractions (r2>0.81). Specific antioxidants were correlated with sweet, fruity and chicken aromas, and -tocopherol inversely with lipid oxidation. PLS2 confirmed relationships between fatty acid composition, antioxidants and the subsets of 32 and 10 flavour components. Clear relationships were thus observed between lipid and antioxidant compositions and flavour in chicken breast meat.