Emet S.,University of Turku |
Knuutila T.,University of Turku |
Alhoniemi E.,University of Turku |
Maier M.,University of Turku |
And 2 more authors.
International Journal of Advanced Manufacturing Technology | Year: 2010
Line balancing of a printed circuit board (PCB) assembly line is considered in the present paper. The production line consists of a number of machines for inserting electronic components on bare PCBs. The aim is to distribute the assembly operations of a single PCB type to the different machines in such a way that the throughput (i.e., the number of finished PCBs per time unit) of the line is maximized. We suppose that the total time for placements is a linear function of the number of component insertions performed by a machine. Effective mathematical formulations of the balancing problem are then available but previous models omit several aspects having an effect on the actual placement times. In particular, we extend an existing MILP formulation of the problem to consider the usage of feeder modules, precedence constraints among the placement operations, and duplication of frequently used components in several machines. We consider production lines consisting of several gantry-type placement machines. Unlike previous research, we applied standard optimization tools for solving the balancing problems. We then observed that the CPLEX-software was able to solve MILP formulations of 2- and 3-machine problems with up to 150 different component types and relatively large number of component placements (from 400 to 6,000). On the other hand, the running time was rather unstable so that heuristics are still needed for cases where exact methods fail. © 2010 Springer-Verlag London Limited.
Raduly-Baka C.,Elcoteq Design Center Oy |
Knuutila T.,University of Turku |
Johnsson M.,Valor Computerized Systems |
Nevalainen O.S.,University of Turku
Computers and Operations Research | Year: 2010
With a great variation of products, PCB assembling machines must be reconfigured often, but at the same time the efficiency of the assembly process should be kept high. In this paper we consider PCB assembly machines of the radial type, which are used for manufacturing robust electronics devices. In this machine type the components are brought to the assembly point by the means of a single component tape, and a robotic arm places them onto a bare PCB one at a time. The component tape is constructed on-line by a separate feeder unit (sequencer) composed of a set of slots storing component reels of various types. While the insertion of components to the tape does not normally delay their placements on the PCB, certain (broad) components delay the processing due to the operation principle of the sequencer, thus increasing the manufacturing time. We study the problem of assigning components to the sequencer in such a way that tape construction delay is minimized, give an integer programming formulation of the problem, and present an optimization algorithm to reduce the component insertion time caused by slow components. The results of this optimization algorithm show considerable improvement against a simple feeder assignment, in case of tape instances containing repeating sequences of components. © 2009 Elsevier Ltd. All rights reserved.
Vainio F.,Turku Center for Computer Science |
Maier M.,Turku Center for Computer Science |
Knuutila T.,Turku Center for Computer Science |
Alhoniemi E.,Turku Center for Computer Science |
And 2 more authors.
International Journal of Production Research | Year: 2010
Several production planning tasks in the printed circuit board (PCB) assembly industry involve the estimation of the component placement times for different PCB types and placement machines. This kind of task may be, for example, the scheduling of jobs or line balancing for single or multiple jobs. The simplest approach to time estimation is to let the production time be a linear function of the number of components to be placed. To achieve more accurate results, the model should include more parameters (e.g. the number of different component types, the number of different component shapes, the dimensions of the PCBs, etc.). In this study we train multilayer neural networks to approximate the assembly times of two different types of assembly machines based on several parameter combinations. It turns out that conventional learning methods are prone to overfitting when the number of hidden units of the network is large in relation to the number of training cases. To avoid this and complicated training and testing, we use Bayesian regularisation to achieve efficient learning and good accuracy automatically. © 2010 Taylor & Francis.
Isaac J.,Mentor Graphics |
Isbell B.,Valor Computerized Systems
Printed Circuit Design and Fab | Year: 2010
The continuum process of design and manufacturing during the electronics product development is included in best-practice DfM rules, preventing failures. The DfM requires communication between the designer and the rest of the supply chain, including procurement, assembly, and test through a bill of materials (BoM). In the DfM process, fabricators run their golden software and fabrication rules against the data to ensure the production of boards and determine adjustments to avoid soft failures that could decrease production yields. Manufacturers are utilizing simulation software to simulate various line configurations combined with various product volumes and product mixes. Managing the assembly line in DfM includes registering and labeling materials, streamlining material preparation, and tracking and controlling production.