Abstract: This research investigates the distribution of food
demand for animal food and the optimum amount of that food
production at minimum cost. The data consist of customer purchase
orders for the food of laying hens, price of food for laying hens, cost
per unit for the food inventory, cost related to food of laying hens in
which the food is out of stock, such as fine, overtime, urgent
purchase for material. They were collected from January, 1990 to
December, 2013 from a factory in Nakhonratchasima province. The
collected data are analyzed in order to explore the distribution of the
monthly food demand for the laying hens and to see the rate of
inventory per unit. The results are used in a stochastic linear
programming model for aggregate planning in which the optimum
production or minimum cost could be obtained. Programming
algorithms in MATLAB and tools in Linprog software are used to get
the solution. The distribution of the food demand for laying hens and
the random numbers are used in the model. The study shows that the
distribution of monthly food demand for laying has a normal
distribution, the monthly average amount (unit: 30 kg) of production
from January to December. The minimum total cost average for 12
months is Baht 62,329,181.77. Therefore, the production planning
can reduce the cost by 14.64% from real cost.
Abstract: Several researches have been conducted to study
consumption of energy in cutting process. Most of these researches
are focusing to measure the consumption and propose consumption
reduction methods. In this work, the relation between the cutting
parameters and the consumption is investigated in order to establish a
generalized energy consumption model that can be used for process
and production planning in real production lines. Using the
generalized model, the process planning will be carried out by taking
into account the energy as a function of the selected process
parameters. Similarly, the generalized model can be used in
production planning to select the right operational parameters like
batch sizes, routing, buffer size, etc. in a production line. The
description and derivation of the model as well as a case study are
given in this paper to illustrate the applicability and validity of the
model.
Abstract: This work addresses the problem of production planning that arises in the production of aromatic coconuts from Samudsakhorn province in Thailand. The planning involves the forwarding of aromatic coconuts from the harvest areas to the factory, which is classified into two groups; self-owned areas and contracted areas, the decisions of aromatic coconuts flow in the plant, and addressing a question of which warehouse will be in use. The problem is formulated as a mixed-integer linear programming model within supply chain management framework. The objective function seeks to minimize the total cost including the harvesting, labor and inventory costs. Constraints on the system include the production activities in the company and demand requirements. Numerical results are presented to demonstrate the feasibility of coconuts supply chain model compared with base case.
Abstract: For years now, it has been recognized that logistic performance capability contributes enormously to a production enterprise’s competitiveness and as such is a critical control lever. In doing so, the orientation on customer wishes (e.g. delivery dates) represents a key parameter not only in the value-adding production but also in product regeneration. Since production and regeneration processes have different characteristics, production planning and control measures cannot be directly transferred to regeneration processes. As part of a special research project, the Institute of Production Systems and Logistics Hannover is focused on increasing the logistic performance capability of regeneration processes for complex capital goods. The aim is to ensure logistic targets are met by implementing a model specifically designed to align the capacities and load in regeneration processes.
Abstract: This paper deals with modeling and optimization of two NP-hard problems in production planning of flexible manufacturing system (FMS), part type selection problem and loading problem. The part type selection problem and the loading problem are strongly related and heavily influence the system’s efficiency and productivity. These problems have been modeled and solved simultaneously by using real coded genetic algorithms (RCGA) which uses an array of real numbers as chromosome representation. The novel proposed chromosome representation produces only feasible solutions which minimize a computational time needed by GA to push its population toward feasible search space or repair infeasible chromosomes. The proposed RCGA improves the FMS performance by considering two objectives, maximizing system throughput and maintaining the balance of the system (minimizing system unbalance). The resulted objective values are compared to the optimum values produced by branch-and-bound method. The experiments show that the proposed RCGA could reach near optimum solutions in a reasonable amount of time.
Abstract: In times of global warming and the increasing
shortage of resources, sustainable production is becoming more and
more inevitable. Companies cannot only heighten their
competitiveness but also contribute positively to environmental
protection through efficient energy and resource consumption.
Regarding this, technical solutions are often preferred during
production, although organizational and process-related approaches
also offer great potential. This project focuses on reducing resource
usage, with a special emphasis on the human factor. It is the
aspiration to develop a methodology that systematically implements
and embeds suitable and individual measures and methods regarding
resource efficiency throughout the entire production. The measures
and methods established help employees handle resources and energy
more sensitively. With this in mind, this paper also deals with the
difficulties that can occur during the sensitization of employees and
the implementation of these measures and methods. In addition,
recommendations are given on how to avoid such difficulties.
Abstract: The planning in manufacturing system is becoming complicated day by day due to the expanding networks and shortage of skilled people to manage change. Consequently, faster lead time and rising demands for eco-efficient evaluation of manufacturing products and processes need exploitation of new and intelligent knowledge management concepts for manufacturing planning. This paper highlights motivation for incorporation of new features in the manufacturing planning system. Furthermore, it elaborates requirements for the development of intelligent knowledge management concept to support planning related decisions. Afterwards, the derived concept is presented in this paper considering two case studies. The first case study is concerned with the automotive ramp-up planning. The second case study specifies requirements for knowledge management system to support decisions in eco-efficient evaluation of manufacturing products and processes
Abstract: Due to the growing dynamic and complexity within
the market environment production enterprises in particular are faced
with new logistic challenges. Moreover, it is here in this dynamic
environment that the Logistic Operating Curve Theory also reaches
its limits as a method for describing the correlations between the
logistic objectives. In order to convert this theory into a method for
dynamically monitoring productions this paper will introduce
methods for reliably and quickly identifying structural changes
relevant to logistics.
Abstract: One of the most important problems in production planning of flexible manufacturing system (FMS) is machine tool selection and operation allocation problem that directly influences the production costs and times .In this paper minimizing machining cost, set-up cost and material handling cost as a multi-objective problem in flexible manufacturing systems environment are considered. We present a 0-1 integer linear programming model for the multiobjective machine tool selection and operation allocation problem and due to the large scale nature of the problem, solving the problem to obtain optimal solution in a reasonable time is infeasible, Paretoant colony optimization (P-ACO) approach for solving the multiobjective problem in reasonable time is developed. Experimental results indicate effectiveness of the proposed algorithm for solving the problem.
Abstract: This paper and its companion (Part 2) deal with
modeling and optimization of two NP-hard problems in production
planning of flexible manufacturing system (FMS), part type selection
problem and loading problem. The part type selection problem and
the loading problem are strongly related and heavily influence the
system-s efficiency and productivity. The complexity of the problems
is harder when flexibilities of operations such as the possibility of
operation processed on alternative machines with alternative tools are
considered. These problems have been modeled and solved
simultaneously by using real coded genetic algorithms (RCGA)
which uses an array of real numbers as chromosome representation.
These real numbers can be converted into part type sequence and
machines that are used to process the part types. This first part of the
papers focuses on the modeling of the problems and discussing how
the novel chromosome representation can be applied to solve the
problems. The second part will discuss the effectiveness of the
RCGA to solve various test bed problems.
Abstract: Producing companies aspire to high delivery
availability despite appearing disruptions. To ensure high delivery
availability safety stocksare required. Howeversafety stock leads to
additional capital commitment and compensates disruptions instead
of solving the reasons.The intention is to increase the stability in
production by configuring the production planning and control
systematically. Thus the safety stock can be reduced. The largest
proportion of inventory in producing companies is caused by batch
inventory, schedule deviations and variability of demand rates.These
reasons for high inventory levels can be reduced by configuring the
production planning and control specifically. Hence the inventory
level can be reduced. This is enabled by synchronizing the lot size
straightening the demand as well as optimizing the releasing order,
sequencing and capacity control.
Abstract: Compost manufacturing plants are one of units where
wastewater is produced in significantly large amounts. Wastewater
produced in these plants contains high amounts of substrate (organic
loads) and is classified as stringent waste which creates significant
pollution when discharged into the environment without treatment. A
compost production plant in the one of the Iran-s province treating
200 tons/day of waste is one of the most important environmental
pollutant operations in this zone. The main objectives of this paper
are to investigate the compost wastewater treatability in hybrid
anaerobic reactors with an upflow-downflow arrangement, to
determine the kinetic constants, and eventually to obtain an
appropriate mathematical model. After starting the hybrid anaerobic
reactor of the compost production plant, the average COD removal
rate efficiency was 95%.
Abstract: In this article, the design of a Supply Chain Network
(SCN) consisting of several suppliers, production plants, distribution
centers and retailers, is considered. Demands of retailers are
considered stochastic parameters, so we generate amounts of data via
simulation to extract a few demand scenarios. Then a mixed integer
two-stage programming model is developed to optimize
simultaneously two objectives: (1) minimization the fixed and
variable cost, (2) maximization the service level. A weighting method
is utilized to solve this two objective problem and a numerical
example is made to show the performance of the model.
Abstract: The authors of this work indicate by means of a concrete example that it is possible to apply efficaciously the method of multiple criteria programming in dealing with the problem of determining the optimal production plan for a certain period of time. The work presents: (1) the selection of optimization criteria, (2) the setting of the problem of determining an optimal production plan, (3) the setting of the model of multiple criteria programming in finding a solution to a given problem, (4) the revised surrogate trade-off method, (5) generalized multicriteria model for solving production planning problem and problem of choosing technological variants in the metal manufacturing industry. In the final part of this work the authors reflect on the application of the method of multiple criteria programming while determining the optimal production plan in manufacturing enterprises.
Abstract: In this paper, we propose a fuzzy aggregate
production planning (APP) model for blending problem in a brass
factory which is the problem of computing optimal amounts of raw
materials for the total production of several types of brass in a
period. The model has deterministic and imprecise parameters
which follows triangular possibility distributions. The brass casting
APP model can not always be solved by using common approaches
used in the literature. Therefore a mathematical model is presented
for solving this problem. In the proposed model, the Lai and
Hwang-s fuzzy ranking concept is relaxed by using one constraint
instead of three constraints. An application of the brass casting
APP model in a brass factory shows that the proposed model
successfully solves the multi-blend problem in casting process and
determines the optimal raw material purchasing policies.
Abstract: In production planning (PP) periods with excess capacity
and growing demand, the manufacturers have two options to use the excess capacity. First, it could do more changeovers and thus reduce lot sizes, inventories, and inventory costs. Second, it could produce in excess of demand in the period and build additional inventory that can be used to satisfy future demand increments, thus
delaying the purchase of the next machine that is required to meet the growth in demand. In this study we propose an enhanced supply
chain planning model with flexible planning capability. In addition, a 3D supply chain planning system is illustrated.
Abstract: Among the numerous economic evaluation techniques currently available, Multi-criteria Spatial Analysis lends itself to solving localization problems of property complexes and, in particular, production plants. The methodology involves the use of Geographical Information Systems (GIS) and the mapping overlay technique, which overlaps the different information layers of a territory in order to obtain an overview of the parameters that characterize it. This first phase is used to detect possible settlement surfaces of a new agglomeration, subsequently selected through Analytic Hierarchy Process (AHP), so as to choose the best alternative. The result ensures the synthesis of a multidimensional profile that expresses both the quantitative and qualitative effects. Each criterion can be given a different weight.
Abstract: This paper investigates the optimization problem of
multi-product aggregate production planning (APP) with fuzzy data.
From a comprehensive viewpoint of conserving the fuzziness of input
information, this paper proposes a method that can completely
describe the membership function of the performance measure. The
idea is based on the well-known Zadeh-s extension principle which
plays an important role in fuzzy theory. In the proposed solution
procedure, a pair of mathematical programs parameterized by
possibility level a is formulated to calculate the bounds of the
optimal performance measure at a . Then the membership function of
the optimal performance measure is constructed by enumerating
different values of a . Solutions obtained from the proposed method
contain more information, and can offer more chance to achieve the
feasible disaggregate plan. This is helpful to the decision-maker in
practical applications.
Abstract: Higher productivity and less cost in the ship
manufacturing process are required to maintain the international
competitiveness of morden manufacturing industries. In shipbuilding,
however, the Engineering To Order (ETO) production method and
production process is very difficult. Thus, designs change frequently.
In accordance with production, planning should be set up according
to scene changes. Therefore, fixed production planning is very
difficult. Thus, a scheduler must first make sketchy plans, then
change the plans based on the work progress and modifications.
Thus, data sharing in a shipbuilding block assembly shop is very
important. In this paper, we proposed to scheduling method
applicable to the shipbuilding industry and decision making support
system through web based visualization system.
Abstract: CONWIP (constant work-in-process) as a pull
production system have been widely studied by researchers to date.
The CONWIP pull production system is an alternative to pure push
and pure pull production systems. It lowers and controls inventory
levels which make the throughput better, reduces production lead
time, delivery reliability and utilization of work. In this article a
CONWIP pull production system was simulated. It was simulated
push and pull planning system. To compare these systems via a
production planning system (PPS) game were adjusted parameters of
each production planning system. The main target was to reduce the
total WIP and achieve throughput and delivery reliability to
minimum values. Data was recorded and evaluated. A future state
was made for real production of plastic components and the setup of
the two indicators with CONWIP pull production system which can
greatly help the company to be more competitive on the market.