One of the most important business areas of the company is the management of working capital. Energy companies that produce electricity and heat are the main consumers of steam coal, so their decision concerning stock levels is a major determinant of supply schedules. These decisions depend on legal and technical requirements as well as economic aspects. The seasonality of coal consumption jointly with pre-purchase costs and storage costs has a straight impact on delivery scheduling in a parabolic way. There is a divergence in expectations regarding delivery schedules among the coal market participants (energy, mining, transport companies). The purpose of this article is to present the concept of pricing of steam coal and transport service on the Polish market, assuming the use of price incentives, resulting in delivery scheduling during the year. The article presents selected theoretical content in the field of coal logistics and working capital management in the company, the expectations of the steam coal market participant regarding delivery schedules have been identified. The proposed concept of pricing steam coal and transport service should be discussed further in scientific and expert work.
The scientific goal of this article was to confirm the thesis that efficient complaint management
can be one the company’s competitive advantage elements of in the sphere of logistic
customer service. The theoretical part of the article presents basic foundations related to
complaint management process as an important element of post-trade sales process in customer
service. The research part presents an example of the implementation of efficient
assumptions of the complaint management process on the example of a construction industry
manufacturing company. Guidelines for the design and implementation of an effective
and efficient complaint handling process are presented. An example of process analysis is
done using appropriate quality tools.
In recent time, as the Chinese consumption level increases, the consumption quantity of high-value fruits, vegetables and seafood products have been increasing year by year. As a consequence, the traffic volume of refrigerated products also increases yearly and the popularization degree of the cold-chain transportation enhances. A low-temperature environment should be guaranteed during transportation, thus there is about 40% of diesel oil should be consumed by the refrigerating system and the cold-chain transportation becomes very costly. This study aimed to explore methods that could reduce the cost of transport packages of refrigerated products. On the basis of the heat transfer theory and the fluid mechanics theory, the heat exchanging process of corrugated cases during the operation of refrigerating system was analyzed, the heat transfer process of corrugated cases and refrigerator van was theoretically analyzed and the heat balance equation of corrugated cases was constructed.
As experience shows the practical, reliable assessment and optimisation of total costs of logistical processes implemented in supply chains
of foundry plants is a quite complex and complicated process, because it requires to enclose all, without exception, performed actions,
including them in various reference cross-sections, systematic activities and finally transforming them in a totally homogenous collection.
Only solid analysis and assessment of assortment management in logistical supply systems in foundry plants of particular assortment
groups allows to lower the supply costs significantly. In the article the analysis and assessment of the newest implemented optimising
algorithms are presented in the process stock management of selected material groups used in a production process of a chosen foundry
plant. A practical solution to solve a problem of rotary stock cost minimisation is given as well as of costs while creating a stock with the
usage of economical volume and value of order.
It has been found that the area where one can look for significant reserves in the procurement logistics is a rational management
of the stock of raw materials. Currently, the main purpose of projects which increase the efficiency of inventory management is to
rationalise all the activities in this area, taking into account and minimising at the same time the total inventory costs. The paper presents
a method for optimising the inventory level of raw materials under a foundry plant conditions using two different control models. The first
model is based on the estimate of an optimal level of the minimum emergency stock of raw materials, giving information about the need
for an order to be placed immediately and about the optimal size of consignments ordered after the minimum emergency level has
occurred. The second model is based on the estimate of a maximum inventory level of raw materials and an optimal order cycle.
Optimisation of the presented models has been based on the previously done selection and use of rational methods for forecasting the time
series of the delivery of a chosen auxiliary material (ceramic filters) to a casting plant, including forecasting a mean size of the delivered
batch of products and its standard deviation
The objectives of this study were to develop a framework of the collaboration network, operational
performance, and reverse logistics determinants on the performance outcomes of the
auto parts industry, and to study the direct, indirect, and overall effects of the factors that
influence the performance outcomes of the auto parts industry. This quantitative research
utilized a questionnaire as the tool for data collection, which was completed by the managers
in the auto parts industry from 320 companies. According to the analysis with the Structural
Equation Modeling (SEM), it was found that the collaboration networks, operational
performance, and reverse logistics positively affect the performance outcomes; whereas, the
collaboration networks mainly affect the development of organizations by causing performance
outcomes to continue growing unceasingly, including the enhancement of sustainable
competitive capacity and the operational results of the auto parts industry.
This study demonstrates application of Lean techniques to improve working process in
a sewing machine factory, focusing on the raw material picking process. The value stream
mapping and flow process chart techniques were utilized to identify the value added activities,
non-value activities and necessary but non-value added activities in the current
process. The ECRS (Eliminate, Combine, Rearrange and Simplify) in waste reduction was
subsequently applied to improve the working process by (i) adjusting the raw material picking
procedures and pre-packing raw material as per demand, (ii) adding symbols onto the
containers to reduce time spent in picking material based on visual control principle, and
(iii) developing and zoning storage area, identifying level location for each row and also
applying algorithms generated from a solver program and linear programming to appropriately
define the location of raw material storage. Improvement in the raw material picking
process was realized, cutting down six out of 11 procedures in material picking or by 55%,
reducing material picking time from 24 to 4 min or by 83%. The distance to handle material
in the warehouse can be shortened by 120 m per time or 2,400 m per day, equal to 86%
reduction. Lean techniques
The field of academic research on corporate sustainability management has gained significant
sophistication since the economic growth has been associated with innovation. In this paper,
we are to show our research project that aims to build an artificial intelligence-based neurofuzzy
inference system to be able to approximate company’s innovation performance, thus
the sustainability innovation potential. For this we used an empirical sample of Hungarian
processing industry’s large companies and built an adaptive neuro fuzzy inference system.
Within the INMOP 3 research project, an attempt was made to solve a number of problems associated with the methodology of modelling travel in urban areas and the application of intermodal models. One of these is the ability to describe the behaviour of transport system users, when it comes to making decisions regarding the selection of means of transport and searching for relationships between travel describing factors and the decisions made in regard of means of transport choice.
The paper describes a probabilistic approach to the determination of modal split, and the application of a logistic regression model to determine the impact of variables describing individual and mass transport travels on the probability of selecting specific means of transport. Travels in local model of Warsaw city divided into 9 motivation groups were tested, for which ultimately 8 models were developed, out of which 7 were deemed very well fitted (obtained pseudoR2 was well above 0.2).
The paper refers to planning deliveries of food products (especially those available in certain seasons) to the recipients: supermarket networks. The paper presents two approaches to solving problems of simultaneous selection of suppliers and transportation modes and construction of product flow schedules with these transportation modes. Linear mathematical models have been built for the presented solution approaches. The cost criterion has been taken into consideration in them. The following costs have been taken into account: purchase of products by individual recipients, transport services, storing of products supplied before the planned deadlines and penalties for delays in supply of products. Two solution approaches (used for transportation planning and selection of suppliers and selection of transportation modes) have been compared. The monolithic approach calls for simultaneous solutions for the problems of supplier selection and selection of transportation modes. In the alternative (hierarchical) solution approach, suppliers are selected first, and then transportation companies and their relevant transportation modes are selected. The results of computational experiments are used for comparison of the hierarchical and monolithic solution approaches.
Cross-docking is a strategy that distributes products directly from a supplier or manufacturing plant to a customer or retail chain, reducing handling or storage time. This study focuses on the truck scheduling problem, which consists of assigning each truck to a door at the dock and determining the sequences for the trucks at each door considering the time-window aspect. The study presents a mathematical model for door assignment and truck scheduling with time windows at multi-door cross-docking centers. The objective of the model is to minimize the overall earliness and tardiness for outbound trucks. Simulated annealing (SA) and tabu search (TS) algorithms are proposed to solve large-sized problems. The results of the mathematical model and of meta-heuristic algorithms are compared by generating test problems for different sizes. A decision support system (DSS) is also designed for the truck scheduling problem for multi-door cross-docking centers. Computational results show that TS and SA algorithms are efficient in solving large-sized problems in a reasonable time.
The implementation of milk-run in Indonesia has been started since 2005. As a developing
country, there is a challenge to operate milk-run smoothly especially in urban area due to
severe traffic congestion and unfavourable road condition in some areas. This research aimed
to analyze the practice of milk-run operation in one of the biggest Japanese automotive
companies in Indonesia. Transportation Value Stream Mapping (TVSM) is applied in order
to perform just-in-time delivery in the supply chain before operating milk-run. It is discussed
that this company still need to continue in improving milk-run operation. The operation
system needs control and integration from manufacturer, supplier and logistics partner.
The advantage of milk-run operation is cost reduction and also support green logistics in
decreasing emission of carbondioxide (CO2) by reducing the number of trucks used.
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