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Purpose: Existing productivity improvements activities such as inventory buffer, overall equipment effectiveness (OEE) and total productive maintenance (TPM) do not analytically associate the throughput shortage with process parameters. The paper aims to develop and test an integrated model to recover the throughput shortage through process parameters adjustment in a semiconductor assembly. Design/methodology/approach: The mathematical model of planned throughput is developed as a function of input parameters in an integrated multiple process line. When the planned throughput does not meet the real-time throughput, the throughput shortage occurs. The planned throughput for the next day is summed with the throughput shortage from previous day and mathematical programming is used to find the optimum process parameter values. Findings: The throughput shortage is restored using mathematical programming for the subsequent day of planning. If there still exist throughput shortage, the additional throughput shortage will be carried forward for the subsequent day of planning where mathematical programming is used again to find the adjusted process parameters. The proposed optimization model in essentially a parametric model using input parameters of real-time data based on a normal distribution that is translated into a range of minimum and maximum using 95% confidence interval. Research limitations/implications: The adjusted input parameters in this model is based on the cycle time of three processes which are Die Attach, Wire Bond and Pre-Cap Inspection. Downtime and setup time are not subjected to adjustments. Practical implications: The mathematical programming computes optimum process parameters values to restore the throughput shortage where it correlates the process parameters and throughput shortage quantitatively rather than conventional method of throughput shortage recovery. Originality/value: The research addresses the process parameter adjustment to recover the throughput shortage in integrated multiple processes.

Thermoelectric Generator (TEG) provides unique advantages as compared to other heat engines as it is capable to convert heat to electricity directly without having any moving parts. Furthermore, TEG is compact, simple and noiseless and requires very minimal maintenance. This paper presents an experimental and analytical study of a model consisting of a TEG located between a copper water cooling jacket and an aluminium block which acts as a heat spreader. The copper water cooling jacket was used in this study as water has higher thermal capacity than air. Besides, copper is one of highest thermal conductivity materials. TEG characterisation in term of electrical was investigated in this study. Based on the result, it shows a linear proportion relationship between open-circuit voltage and temperature difference across TEG. The result also clearly shows the power output of TEG increases as the temperature gradient across TEG increases. In addition, the impact of water flowrate on TEG power output was also studied. Based on the finding, there was an optimum water flowrate of 80 ml/s. Further increasing the water flowrate is not favourable as it will not increase power output and may lead to higher pumping power for water circulation. At this optimum water flowrate, the maximum power output obtained is equal to 530 mW when TEG hot-side temperature (Th) is 180 °C. [ABSTRACT FROM AUTHOR]

Purpose: Existing productivity improvements activities such as inventory buffer, overall equipment effectiveness (OEE) and total productive maintenance (TPM) do not associate the throughput shortage with the process parameters. The paper aims to develop and validate an integrated model to recover the throughput shortage through adjustment of process parameters in a semiconductor assembly setting. Design/methodology/approach: The mathematical model of planned throughput as a function of process parameters in an integrated multiple-process line is developed. When the actual throughput does not meet the planned throughput, throughput shortage occurs. The planned throughput for the next day is summed with the throughput shortage from the previous day, and mathematical programming is used to search the adjusted values of the process parameters. Findings: The throughput shortage can be restored at the following day with the reconfigured process parameters. If throughput shortage still exists, the additional throughput shortage will be carried forward to the subsequent day of planning where mathematical programming is repeated to search the adjusted values of the process parameters. The proposed optimisation model is essentially a parametric model, where actual data of process parameters are fitted into distribution and is translated into a range of allowable values within the 95% confidence interval. Research limitations/implications: The process parameters subject to adjustment in this model are the cycle time of Die Attach, Wire Bond and Pre-Cap Inspection. Downtime and setup time are not subjected to adjustments because these parameters require more extensive efforts to be changed. Practical implications: The mathematical programming computes adjusted values of process parameters to restore the throughput shortage, where it quantitatively correlates the process parameters and throughput shortage, rather than the conventional method of production improvement activities that do not quantitatively correlate with the throughput shortage. Originality/value: The research addresses the adjustment of process parameters to recover the throughput shortage in integrated multiple-process line. [ABSTRACT FROM AUTHOR]

The composite PCM was prepared by blending polymethyl methacrylate (PMMA) and myristic acid (MA) in different weight percentages. The MA and PMMA were selected as PCM and supporting material, respectively. As liquid MA may leak out during the phase transition, this study proposes the use of two coatings, namely a polyacrylic coating and a conformal coating to overcome the leakage problem. Both coatings were studied in terms of the leakage test, chemical compatibility, thermal stability, morphology, and reliability. No leakage was found in the PCMs with coatings compared to those without under the same proportions of MA/PMMA, thus justifying the use of coatings in the present study. The chemically compatibility was confirmed by FTIR spectra: the functional groups of PCMs were in accordance with those of coatings. DSC showed that the coatings did not significantly change the melting and freezing temperatures, however, they improved the thermal stability of composite PCMs as seen in TGA analysis. Furthermore, the composite PCMs demonstrated good thermal reliability after 1000 times thermal cycling. The latent heat of melting reduced by only 0.16% and 1.02% for the PCMs coated with conformal coating and polyacrylic coating, respectively. Therefore, the proposed coatings can be considered in preparing fatty acid/PMMA blends attributed to the good stability, compatibility and leakage prevention., Competing Interests: The authors declare no conflict of interest.

In this study, reduced graphene oxide (RGO)/polymethyl methacrylate (PMMA) nanocomposites were prepared by employing in situ polymerization and solution blending methods. In terms of mechanical properties, RGO loading increased the Young's modulus but decreased the elongation at break for RGO/PMMA nanocomposites. Tensile strength for solution blended RGO/PMMA nanocomposites increased after adding 0.5 wt % RGO, which was attributed to the good dispersion of RGO in the nanocomposites as evidenced from SEM and TEM. Solar energy conversion efficiency measurement results showed that the optimum concentration of RGO in the RGO/PMMA nanocomposites was found to be 1.0 wt % in order to achieve the maximum solar energy conversion efficiency of 25%. In the present study, the solution blended nanocomposites exhibited better overall properties than in situ polymerized nanocomposites owing to the better dispersion of RGO in solution blending. These findings would contribute to future work in search of higher conversion efficiency using nanocomposites., Competing Interests: The authors declare no conflict of interest.