International Science Index

11
10007809
The Effects of Plantation Size and Internal Transport on Energy Efficiency of Biofuel Production
Abstract:

Mathematical model describing energetic efficiency (defined as a ratio of energy obtained in the form of biofuel to the sum of energy inputs necessary to facilitate production) of agricultural subsystem as a function of technological parameters was developed. Production technology is characterized by parameters of machinery, topological characteristics of the plantation as well as transportation routes inside and outside of plantation. The relationship between the energetic efficiency of agricultural and industrial subsystems is also derived. Due to the assumed large area of the individual field, the operations last for several days increasing inter-fields routes because of several returns. The total distance driven outside of the fields is, however, small as compared to the distance driven inside of the fields. This results in small energy consumption during inter-fields transport that, however, causes a substantial decrease of the energetic effectiveness of the whole system.

Paper Detail
4
downloads
10
9999830
Safety of Industrial Networks
Abstract:

The paper deals with communication standards for control and production system. The authors formulate the requirements for communication security protection. The paper is focused on application protocols of the industrial networks and their basic classification. The typical attacks are analysed and the safety protection, based on requirements for specific industrial network is suggested and defined in this paper.

Paper Detail
1275
downloads
9
17184
Assessing and Improving Ramp-Up Capability
Abstract:

In times when product life cycles are decreasing, while market demands are increasing, manufacturing enterprises are confronted with the challenge of more frequent and more complex ramp-ups. Thus it becomes obvious that ramp-up management is going to be a topic enterprises have to focus on in the future. Since each ramp-up is unique concerning the product, the process, the technology, the circumstances and the coaction of these four factors, the knowledge of the ramp-up situation and the current ramp-up capability of the enterprise are fundamental requirements for the subsequent improvement of the ramp-up capability of the production system.

In this article a methodology is going to be presented which can be used to define typical production ramp-up situations, to identify the current ramp-up capability of a production system and to improve it with respect to a specific situation. Additionally there will be a description of the functionality of a software-tool developed based on this methodology.

Paper Detail
1263
downloads
8
9997606
Cost Sensitive Analysis of Production Logistics Measures A Decision Making Support System for Evaluating Measures in the Production
Abstract:

Due to the volatile global economy, enterprises are increasingly focusing on logistics. By investing in suitable measures a company can increase their logistic performance and assert themselves over the competition. However, enterprises are also faced with the challenge of investing available capital for maximum profits. In order to be able to create an informed and quantifiably comprehensible basis for a decision, enterprises need a suitable model for logistically and monetarily evaluating measures in production. Previously, within the frame of Collaborate Research Centre 489 (SFB 489) at the Institute for Production Systems and Logistics, (IFA) a Logistic Information System was developed specifically for providing enterprises in the forging industry with support when making decisions. Based on this research, a new initiative referred to as ‘Transfer Project T7’, aims to develop a universal approach for logistically and monetarily evaluating production measures. This paper focuses on the structural measure echelon storage and their impact on the entire production system.

Paper Detail
677
downloads
7
5790
Applying Lean Principles, Tools and Techniques in Set Parts Supply Implementation
Abstract:
Lean, which was initially developed by Toyota, is widely implemented in other companies to improve competitiveness. This research is an attempt to identify the adoption of lean in the production system of Malaysian car manufacturer, Proton using case study approach. To gain the in-depth information regarding lean implementation, an activity on the assembly line called Set Parts Supply (SPS) was studied. The result indicates that by using lean principles, tools and techniques in the implementation of SPS enabled to achieve the goals on safety, quality, cost, delivery and morale. The implementation increased the size of the workspace, improved the quality of assembly and the delivery of parts supply, reduced the manpower, achieved cost savings on electricity and also increased the motivation of manpower in respect of attendance at work. A framework of SPS implementation is suggested as a contribution for lean practices in production system.
Paper Detail
3573
downloads
6
9252
Just-In-Time Implementation Status in the Middle East Industry
Authors:
Abstract:
The purpose of this study is to identify and evaluate the scale of implementation of Just-In-Time (JIT) in the different industrial sectors in the Middle East. This study analyzes the empirical data collected by a questionnaire survey distributed to companies in three main industrial sectors in the Middle East, which are: food, chemicals and fabrics. The following main hypotheses is formulated and tested: (The requirements of JIT application differ according to the type of industrial sector).Descriptive statistics and Box plot analysis were used to examine the hypotheses. This study indicates a reasonable evidence for accepting the main hypotheses. It reveals that there is no standard way to adopt JIT as a production system. But each industrial sector should concentrate in the investment on critical requirements that differ according to the nature and strategy of production followed in that sector.
Paper Detail
1326
downloads
5
7551
Production Throughput Modeling under Five Uncertain Variables Using Bayesian Inference
Abstract:

Throughput is an important measure of performance of production system. Analyzing and modeling of production throughput is complex in today-s dynamic production systems due to uncertainties of production system. The main reasons are that uncertainties are materialized when the production line faces changes in setup time, machinery break down, lead time of manufacturing, and scraps. Besides, demand changes are fluctuating from time to time for each product type. These uncertainties affect the production performance. This paper proposes Bayesian inference for throughput modeling under five production uncertainties. Bayesian model utilized prior distributions related to previous information about the uncertainties where likelihood distributions are associated to the observed data. Gibbs sampling algorithm as the robust procedure of Monte Carlo Markov chain was employed for sampling unknown parameters and estimating the posterior mean of uncertainties. The Bayesian model was validated with respect to convergence and efficiency of its outputs. The results presented that the proposed Bayesian models were capable to predict the production throughput with accuracy of 98.3%.

Paper Detail
1315
downloads
4
1718
Hybrid Minimal Repair for a Serial System
Abstract:
This study proposes a hybrid minimal repair policy which combines periodic maintenance policy with age-based maintenance policy for a serial production system. Parameters of such policy are defined as  and  which indicate as hybrid minimal repair time and planned preventive maintenance time respectively  . Under this hybrid policy, the system is repaired minimally if it fails during , . A perfect repair is conducted on the first failure after  at any machines. At the same time, we take opportunity to advance the preventive maintenance of other machines simultaneously. If the system is still operating properly up to , then the preventive maintenance is carried out as its predetermined schedule. For a given , we obtain the optimal value  which minimizes the expected cost per time unit. Numerical example is presented to illustrate the properties of the optimal solution.
Paper Detail
853
downloads
3
7422
The Data Mining usage in Production System Management
Abstract:
The paper gives the pilot results of the project that is oriented on the use of data mining techniques and knowledge discoveries from production systems through them. They have been used in the management of these systems. The simulation models of manufacturing systems have been developed to obtain the necessary data about production. The authors have developed the way of storing data obtained from the simulation models in the data warehouse. Data mining model has been created by using specific methods and selected techniques for defined problems of production system management. The new knowledge has been applied to production management system. Gained knowledge has been tested on simulation models of the production system. An important benefit of the project has been proposal of the new methodology. This methodology is focused on data mining from the databases that store operational data about the production process.
Paper Detail
2461
downloads
2
13185
Study The Effects of Conventional and Low Input Production System on Energy Efficiency of Silybum marianum L.
Abstract:

Medicinal plants are most suitable crops for ecological production systems because of their role in human health and the aim of sustainable agriculture to improve ecosystem efficiency and its products quality. Calculations include energy output (contents of energy in seed) and energy inputs (consumption of fertilizers, pesticides, labor, machines, fuel and electricity). The ratio of output of the production to inputs is called the energy outputs / inputs ratio or energy efficiency. One way to quantify essential parts of agricultural development is the energy flow method. The output / input energy ratio is proposed as the most comprehensive single factor in pursuing the objective of sustainability. Sylibum marianum L. is one of the most important medicinal plants in Iran and has effective role on health of growing population in Iran. The objective of this investigation was to find out energy efficiency in conventional and low input production system of Milk thistle. This investigation was carried out in the spring of 2005 – 2007 in the Research Station of Rangelands in Hamand - Damavand region of IRAN. This experiment was done in split-split plot based on randomized complete block design with 3 replications. Treatments were 2 production systems (Conventional and Low input system) in the main plots, 3 planting time (25 of March, 4 and 14 of April) in the sub plots and 2 seed types (Improved and Native of Khoozestan) in the sub-sub plots. Results showed that in conventional production system energy efficiency, because of higher inputs and less seed yield, was less than low input production system. Seed yield was 1199.5 and 1888 kg/ha in conventional and low input systems, respectively. Total energy inputs and out puts for conventional system was 10068544.5 and 7060515.9 kcal. These amounts for low input system were 9533885.6 and 11113191.8 kcal. Results showed that energy efficiency for seed production in conventional and low input system was 0.7 and 1.16, respectively. So, milk thistle seed production in low input system has 39.6 percent higher energy efficiency than conventional production system. Also, higher energy efficiency were found in sooner planting time (25 of March) and native seed of Khoozestan.

Paper Detail
1000
downloads
1
10797
Machine Learning in Production Systems Design Using Genetic Algorithms
Abstract:
To create a solution for a specific problem in machine learning, the solution is constructed from the data or by use a search method. Genetic algorithms are a model of machine learning that can be used to find nearest optimal solution. While the great advantage of genetic algorithms is the fact that they find a solution through evolution, this is also the biggest disadvantage. Evolution is inductive, in nature life does not evolve towards a good solution but it evolves away from bad circumstances. This can cause a species to evolve into an evolutionary dead end. In order to reduce the effect of this disadvantage we propose a new a learning tool (criteria) which can be included into the genetic algorithms generations to compare the previous population and the current population and then decide whether is effective to continue with the previous population or the current population, the proposed learning tool is called as Keeping Efficient Population (KEP). We applied a GA based on KEP to the production line layout problem, as a result KEP keep the evaluation direction increases and stops any deviation in the evaluation.
Paper Detail
903
downloads