Abstract: Green hydrogen is the most environmental, renewable alternative to produce hydrogen. However, an important challenge to make hydrogen a competitive energy carrier is a constant supply of renewable energy, such as solar, wind and hydropower. Given that the electricity generation potential of these sources vary seasonally and interannually, this paper proposes installing an electrolysis hydrogen production plant in a ship and move the ship to the locations where electricity is cheap, or where the seasonal potential for renewable generation is high. An example of electrolysis ship application is to produce green hydrogen with hydropower from the North region of Brazil and then sail to the Northeast region of Brazil and generate hydrogen using excess electricity from offshore wind power. The electrolysis ship concept is interesting because it has the flexibility to produce green hydrogen using the cheapest renewable electricity available in the market.
Abstract: A major problem that affects the quality control of polymer in the industrial polymerization is the lack of suitable on-line measurement tools to evaluate the properties of the polymer such as melt and density indices. Controlling the polymerization in ordinary method is performed manually by taking samples, measuring the quality of polymer in the lab and registry of results. This method is highly time consuming and leads to producing large number of incompatible products. An online application for estimating melt index and density proposed in this study is a neural network based on the input-output data of the polyethylene production plant. Temperature, the level of reactors' bed, the intensity of ethylene mass flow, hydrogen and butene-1, the molar concentration of ethylene, hydrogen and butene-1 are used for the process to establish the neural model. The neural network is taught based on the actual operational data and back-propagation and Levenberg-Marquart techniques. The simulated results indicate that the neural network process model established with three layers (one hidden layer) for forecasting the density and the four layers for the melt index is able to successfully predict those quality properties.
Abstract: This paper presents a methodology for serial production planning problem in wire and cable manufacturing process that addresses the problem of input-output imbalance in different consecutive stations, hoping to minimize the halt of machines in each stage. To this end, a linear Goal Programming (GP) model is developed, in which four main categories of constraints as per the number of runs per machine, machines’ sequences, acceptable inventories of machines at the end of each period, and the necessity of fulfillment of the customers’ orders are considered. The model is formulated based upon on the real data obtained from IKO TAK Company, an important supplier of wire and cable for oil and gas and automotive industries in Iran. By solving the model in GAMS software the optimal number of runs, end-of-period inventories, and the possible minimum idle time for each machine are calculated. The application of the numerical results in the target company has shown the efficiency of the proposed model and the solution in decreasing the lead time of the end product delivery to the customers by 20%. Accordingly, the developed model could be easily applied in wire and cable companies for the aim of optimal production planning to reduce the halt of machines in manufacturing stages.
Abstract: The linear programming model is sometimes difficult to apply in real business situations due to its assumption of proportionality. This paper shows an example of how to use De Novo programming approach instead of linear programming. In the De Novo programming, resources are not fixed like in linear programming but resource quantities depend only on available budget. Budget is a new, important element of the De Novo approach. Two different production situations are presented: increasing costs and quantity discounts of raw materials. The focus of this paper is on advantages of the De Novo approach in the optimization of production plan for production company which produces souvenirs made from famous stone from the island of Brac, one of the greatest islands from Croatia.
Abstract: Fuzzy AHP (Analytic Hierarchy Process) method is decision-making way at the end of integrating the current AHP method with fuzzy structure. In this study, the processes of production planning, inventory management and purchasing department of a system were analysed and were requested to decide the performance criteria of each area. At this point, the current work processes were analysed by various decision-makers and comparing each criteria by giving points according to 1-9 scale were completed. The criteria were listed in order to their weights by using Fuzzy AHP approach and top three performance criteria of each department were determined. After that, the performance criteria of supply chain consisting of three departments were asked to determine. The processes of each department were compared by decision-makers at the point of building the supply chain performance system and getting the performance criteria. According to the results, the criteria of performance system of supply chain by using Fuzzy AHP were determined for which will be used in the supply chain performance system in the future.
Abstract: To have effective production planning, it is necessary to control the quality of processes. This paper aims at improving the performance of the disposable essentials process using statistical quality control and goal programming in a vague environment. That is expressed uncertainty because there is always a measurement error in the real world. Therefore, in this study, the conditions are examined in a vague environment that is a distance-based environment. The disposable essentials process in Kach Company was studied. Statistical control tools were used to characterize the existing process for four factor responses including the average of disposable glasses’ weights, heights, crater diameters, and volumes. Goal programming was then utilized to find the combination of optimal factors setting in a vague environment which is measured to apply uncertainty of the initial information when some of the parameters of the models are vague; also, the fuzzy regression model is used to predict the responses of the four described factors. Optimization results show that the process capability index values for disposable glasses’ average of weights, heights, crater diameters and volumes were improved. Such increasing the quality of the products and reducing the waste, which will reduce the cost of the finished product, and ultimately will bring customer satisfaction, and this satisfaction, will mean increased sales.
Abstract: In this article, the flexible job-shop scheduling problem is extended by consideration of energy costs which arise owing to the power peak, and further decision variables such as work in process and throughput time are incorporated into the objective function. This enables a production plan to be simultaneously optimized in respect of the real arising energy and logistics costs. The energy-costs-aware flexible job-shop scheduling problem (EFJSP) which arises is described mathematically, and a memetic algorithm (MA) is presented as a solution. In the MA, the evolutionary process is supplemented with a local search. Furthermore, repair procedures are used in order to rectify any infeasible solutions that have arisen in the evolutionary process. The potential for lowering the real arising costs of a production plan through consideration of energy consumption levels is highlighted.
Abstract: In this paper, we suggest a simulation tool to make a decision of monthly production planning for maximizing a profit of Specialty store retailer of Private label Apparel (SPA) firms. Most of SPA firms are fabless and make outsourcing deals for productions with factories of their subcontractors. Every month, SPA firms make a booking for production lines and manpower in the factories. The booking is conducted a few months in advance based on a demand prediction and a monthly production planning at that time. However, the demand prediction is updated month by month, and the monthly production planning would change to meet the latest demand prediction. Then, SPA firms have to change the capacities initially booked within a certain range to suit to the monthly production planning. The booking system is called “capacity-booking”. These days, though it is an issue for SPA firms to make precise monthly production planning, many firms are still conducting the production planning by empirical rules. In addition, it is also a challenge for SPA firms to match their products and factories with considering their demand predictabilities and regulation abilities. In this paper, we suggest a model for considering these two issues. An objective is to maximize a total profit of certain periods, which is sales minus costs of production, inventory, and capacity-booking penalty. To make a better monthly production planning at SPA firms, these points should be considered: demand predictabilities by random trends, previous and next month’s production planning of the target month, and regulation abilities of the capacity-booking. To decide matching products and factories for outsourcing, it is important to consider seasonality, volume, and predictability of each product, production possibility, size, and regulation ability of each factory. SPA firms have to consider these constructions and decide orders with several factories per one product. We modeled these issues as a linear programming. To validate the model, an example of several computational experiments with a SPA firm is presented. We suppose four typical product groups: basic, seasonal (Spring / Summer), seasonal (Fall / Winter), and spot product. As a result of the experiments, a monthly production planning was provided. In the planning, demand predictabilities from random trend are reduced by producing products which are different product types. Moreover, priorities to produce are given to high-margin products. In conclusion, we developed a simulation tool to make a decision of monthly production planning which is useful when the production planning is set every month. We considered the features of capacity-booking, and matching of products and factories which have different features and conditions.
Abstract: Due to shortening product and technology lifecycles, many companies use standardization approaches in product development and factory planning to reduce costs and time to market. Unlike large companies, where modular systems are already widely used, small and medium-sized companies often show a much lower degree of standardization due to lower scale effects and missing capacities for the development of these standards. To overcome these challenges, the development of industry sector specific standards in cooperations or by third parties is an interesting approach. This paper analyzes which branches that are mainly dominated by small or medium-sized companies might be especially interesting for the development of factory standards using the example of the German industry. For this, a key performance indicator based approach was developed that will be presented in detail with its specific results for the German industry structure.
Abstract: Most developing nations face energy production and supply problems. This is also the case of Afghanistan whose generating capacity does not meet its energy demand. This is due in part to high security and risk caused by war which deters foreign investments and insufficient internal revenue. To address the issue above, this paper would like to suggest an alternative and affordable way to deal with the energy problem. That is by converting Solid Waste to energy. As a result, this approach tackles the municipal solid waste issue (potential cause of several diseases), contributes to the improvement of the quality of life, local economy, and so on. While addressing the solid waste problem in general, this paper samples specifically one municipality which is District-12, one of the 22 districts of Kabul city. Using geographic information system (GIS) technology, District-12 is divided into nine different zones whose municipal solid waste is respectively collected, processed, and converted into electricity and distributed to the closest area. It is important to mention that GIS has been used to estimate the amount of electricity to be distributed and to optimally position the production plant.
Abstract: The Flow Shop Scheduling Problem (FSSP) is a typical problem that is faced by production planning managers in Flexible Manufacturing Systems (FMS). This problem consists in finding the optimal scheduling to carry out a set of jobs, which are processed in a set of machines or shared resources. Moreover, all the jobs are processed in the same machine sequence. As in all the scheduling problems, the makespan can be obtained by drawing the Gantt chart according to the operations order, among other alternatives. On this way, an FMS presenting the FSSP can be modeled by Petri nets (PNs), which are a powerful tool that has been used to model and analyze discrete event systems. Then, the makespan can be obtained by simulating the PN through the token game animation and incidence matrix. In this work, we present an adaptive PN to obtain the makespan of FSSP by applying PN analytical tools.
Abstract: Test automation allows performing difficult and time
consuming manual software testing tasks efficiently, quickly and
repeatedly. However, development and maintenance of automated
tests is expensive, so it needs a proper prioritization what to automate
first. This paper describes a simple yet efficient approach for such
prioritization of test cases based on the effort needed for both manual
execution and software test automation. The suggested approach is
very flexible because it allows working with a variety of assessment
methods, and adding or removing new candidates at any time. The
theoretical ideas presented in this article have been successfully
applied in real world situations in several software companies by the
authors and their colleagues including testing of real estate websites,
cryptographic and authentication solutions, OSGi-based middleware
framework that has been applied in various systems for smart homes,
connected cars, production plants, sensors, home appliances, car head
units and engine control units (ECU), vending machines, medical
devices, industry equipment and other devices that either contain or
are connected to an embedded service gateway.
Abstract: Batch production plants provide a wide range of
scheduling problems. In pharmaceutical industries a batch process
is usually described by a recipe, consisting of an ordering of tasks
to produce the desired product. In this research work we focused
on pharmaceutical production processes requiring the culture of
a microorganism population (i.e. bacteria, yeasts or antibiotics).
Several sources of uncertainty may influence the yield of the culture
processes, including (i) low performance and quality of the cultured
microorganism population or (ii) microbial contamination. For
these reasons, robustness is a valuable property for the considered
application context. In particular, a robust schedule will not collapse
immediately when a cell of microorganisms has to be thrown away
due to a microbial contamination. Indeed, a robust schedule should
change locally in small proportions and the overall performance
measure (i.e. makespan, lateness) should change a little if at all.
In this research work we formulated a constraint programming
optimization (COP) model for the robust planning of antibiotics
production. We developed a discrete-time model with a multi-criteria
objective, ordering the different criteria and performing a
lexicographic optimization. A feasible solution of the proposed
COP model is a schedule of a given set of tasks onto available
resources. The schedule has to satisfy tasks precedence constraints,
resource capacity constraints and time constraints. In particular
time constraints model tasks duedates and resource availability
time windows constraints. To improve the schedule robustness, we
modeled the concept of (a, b) super-solutions, where (a, b) are input
parameters of the COP model. An (a, b) super-solution is one in
which if a variables (i.e. the completion times of a culture tasks)
lose their values (i.e. cultures are contaminated), the solution can be
repaired by assigning these variables values with a new values (i.e.
the completion times of a backup culture tasks) and at most b other
variables (i.e. delaying the completion of at most b other tasks).
The efficiency and applicability of the proposed model is
demonstrated by solving instances taken from a real-life
pharmaceutical company. Computational results showed that
the determined super-solutions are near-optimal.
Abstract: The efficient and economic allocation of resources is
one main goal in the field of production planning and control.
Nowadays, a new variable gains in importance throughout the
planning process: Energy. Energy-efficiency has already been widely
discussed in literature, but with a strong focus on reducing the overall
amount of energy used in production. This paper provides a brief
systematic approach, how energy-supply-orientation can be used for
an energy-cost-efficient production planning and thus combining the
idea of energy-efficiency and energy-flexibility.
Abstract: In this paper, the goal programming methodology for
solving multiple objective problem of the technological variants and
production plan optimization has been applied. The optimization
criteria are determined and the multiple objective linear programming
model for solving a problem of the technological variants and
production plan optimization is formed and solved. Then the obtained
results are analysed. The obtained results point out to the possibility
of efficient application of the goal programming methodology in
solving the problem of the technological variants and production plan
optimization. The paper points out on the advantages of the
application of the goal programming methodology compare to the
Surrogat Worth Trade-off method in solving this problem.
Abstract: One of the most famous techniques which affect the
efficiency of a production line is the assembly line balancing (ALB)
technique. This paper examines the balancing effect of a whole
production line of a real auto glass manufacturer in three steps. In the
first step, processing time of each activity in the workstations is
generated according to a practical approach. In the second step, the
whole production process is simulated and the bottleneck stations
have been identified, and finally in the third step, several
improvement scenarios are generated to optimize the system
throughput, and the best one is proposed. The main contribution of
the current research is the proposed framework which combines two
famous approaches including Assembly Line Balancing and
Optimization via Simulation technique (OvS). The results show that
the proposed framework could be applied in practical environments,
easily.
Abstract: An efficient remanufacturing network lead to an
efficient design of sustainable manufacturing enterprise. In
remanufacturing network, products are collected from the customer
zone, disassembled and remanufactured at a suitable remanufacturing
facility. In this respect, another issue to consider is how the returned
product to be remanufactured, in other words, what is the best layout
for such facility. In order to achieve a sustainable manufacturing
system, Cellular Manufacturing System (CMS) designs are highly
recommended, CMSs combine high throughput rates of line layouts
with the flexibility offered by functional layouts (job shop).
Introducing the CMS while designing a remanufacturing network will
benefit the utilization of such a network. This paper presents and
analyzes a comprehensive mathematical model for the design of
Dynamic Cellular Remanufacturing Systems (DCRSs). In this paper,
the proposed model is the first one to date that considers CMS and
remanufacturing system simultaneously. The proposed DCRS model
considers several manufacturing attributes such as multi period
production planning, dynamic system reconfiguration, duplicate
machines, machine capacity, available time for workers, worker
assignments, and machine procurement, where the demand is totally
satisfied from a returned product. A numerical example is presented
to illustrate the proposed model.
Abstract: Power Regeneration in Refrigeration Plant concept
has been analyzed and has been shown to be capable of saving about
25% power in Cryogenic Plants with the Power Regeneration System
(PRS) running under nominal conditions. The innovative component
Compressor Expander Group (CEG) based on turbomachinery has
been designed and built modifying CETT compressor and expander,
both selected for optimum plant performance. Experiments have
shown the good response of the turbomachines to run with R404a as
working fluid. Power saving up to 12% under PRS derated conditions
(50% loading) has been demonstrated. Such experiments allowed
predicting a power saving up to 25% under CEG full load.
Abstract: A well designed and executed Production Planning
and Control (PPC) system is one of the key levers for superior
performance in the current manufacturing set-up. Hence, measuring
the PPC system performance has become a necessity for long term
success. The present study examined PPC related issues which
impact the production capacity and productivity of leather companies
with special focus on Kombolcha Tannery Share Company (KTSC),
Ethiopia. Physical observation, interview, and questionnaire were
used to generate necessary information from the respondents and
reach valid conclusions. Company annual reports were referred and
analyzed to triangulate primary data. Consequently, the study
revealed that KTSC runs below its capacity due to its inefficient PPC
system being in use for which the root causes were identified. The
study thereby conceptualizes a PPC system improvement framework
comprising three pillars viz., management culture, internal capability
and performance measurement together with key considerations in
each case. The study findings enable the company to recognize the
importance of efficient PPC system as a source of competitive
advantage. It also aid managers in evaluating various PPC execution
schemes to enhance productivity.
Abstract: Small and medium-sized enterprises (SME) are the backbone of central Europe’s economies and have a significant contribution to the gross domestic product. Production planning and scheduling (PPS) is still a crucial element in manufacturing industries of the 21st century even though this area of research is more than a century old. The topic of PPS is well researched especially in the context of large enterprises in the manufacturing industry. However the implementation of PPS methodologies within SME is mostly unobserved. This work analyzes how PPS is implemented in SME with the geographical focus on Switzerland and its vicinity. Based on restricted resources compared to large enterprises, SME have to face different challenges. The real problem areas of selected enterprises in regards of PPS are identified and evaluated. For the identified real-life problem areas of SME clear and detailed recommendations are created, covering concepts and best practices and the efficient usage of PPS. Furthermore the economic and entrepreneurial value for companies is lined out and why the implementation of the introduced recommendations is advised.