Nuclear logging is one of major areas of logging development. This paper presents an empirical investigation to bring the drilling and completion of wells from an ill-defined art to a refined sci-ence by using radioactive source to “look and measure” such as formation type, formation dip, porosity, fluid type and numerous other important factors. The initial nuclear logging tools rec-ords the radiation emitted by formation as they were crossed by boreholes. Gamma radiation is used in well logging as it is powerful enough to penetrate the formation and steel casing. The ra-dioactive source is reusable so that after engineer finished the job the radioactive source is sent back to bunker. In this case inventory level of radioactive source is relatively high compared with monthly movement and the company must spend large amount of cost just for inventory. After calculating and averaging the monthly movement in 2014 and 2015, we detected a big pos-sibility to cut the inventory level to reduce the inventory cost.
Polyester short cut fiber is a textile industry which is rarely explored or researched. This research explains the necessary steps of improvement using Six Sigma method to reduce the nonconform-ing products in a polyester short cut fiber manufacturing in Indonesia. An increased noncon-forming products in the shortcut fiber production process created some quality problems from January to May, 2015. Define, measure, analysis, improve, control (DMAIC) steps were im-plemented to determine root cause of the problems and to improve production process using sta-tistical approach. The results of Six Sigma improvement has indicated that the process capability was increased from 2.2 to 3.1 sigma, savings $18,394.2 USD per-month.
This paper discusses an integrated model of batch production and maintenance scheduling on a deteriorating machine producing multiple items to be delivered at a common due date. The model describes the trade-off between total inventory cost and maintenance cost as the increase of production run length. The production run length is a time bucket between two consecutive preventive maintenance activities. The objective function of the model is to minimize total cost consisting of in process and completed part inventory costs, setup cost, preventive and corrective maintenance costs and rework cost. The problem is to determine the optimal production run length and to schedule the batches obtained from determining the production run length in order to minimize total cost.
This research discusses an integer batch scheduling problems for a single-machine with position-dependent batch processing time due to the simultaneous effect of learning and forgetting. The decision variables are the number of batches, batch sizes, and the sequence of the resulting batches. The objective is to minimize total actual flow time, defined as total interval time between the arrival times of parts in all respective batches and their common due date. There are two proposed algorithms to solve the problems. The first is developed by using the Integer Composition method, and it produces an optimal solution. Since the problems can be solved by the first algorithm in a worst-case time complexity O(n2n-1), this research proposes the second algorithm. It is a heuristic algorithm based on the Lagrange Relaxation method. Numerical experiments show that the heuristic algorithm gives outstanding results.
Multi-objective optimization is an optimization problem with some conflicting objectives to be attained, simultanously. This paper reviewed literature about multi-objective optimization problems for supply chain management. The review aimed to provide the lastest research views and recomendations for further studies. We discussed the lastest ten years publications about multi-objective optimization for supply chain management. The scope of this review was classified into five categories i.e. problem statements, multi-objective frameworks, mathematical formulation modeling, optimization techniques, and representation of supply chain. Multi-objective optimization approaches, both classical and metaheuristic approaches, were discussed, accordingly. In this review, we conducted conclusion and recomendations about likelihood research directions in future.
Enzymatic assay, based on oxidation-reduction reaction catalyzed by alcohol dehydrogenase, is one of the methods used to determine ethanol concentration. The present study was directed to determine the exact amount of enzyme required to accomplish oxidation-reduction reaction so that the concentration of ethanol in the sample can be determined precisely and accurately. Results of the present study indicate that the lowest unit activity of the enzyme that can be used for ethanol determination is 4000 units/mL, even though longer incubation time compared to the original method was used to ensure reaction completion. Validation of the method confirmed that the assay have acceptable linearity range within 0.01 - 0.06% (v/v) of ethanol with correlation coefficient of 0.9999. Both accuracy and precision parameters fulfill the Association of Analytical Communities (AOAC) International requirement, and therefore can be accepted as a quantitative analysis method. Limit of detection and limit of quantitation for the modified method were 0.0017% (v/v) and 0.0056% (v/v), respectively.