Renewable synthetic methanol system design based on modular production lines

The existing product line design literature devotes little attention to the effect of demand uncertainty. Due to demand uncertainty, the supply‐demand mismatch is inevitable which leads to different degrees of lost sales depending on the configuration of product lines. In this article, we adopt a stylized two‐segment setup with uncertain market sizes and illustrate the interplay between two effects: risk pooling that mitigates the impact of demand uncertainty and market segmentation that facilitates consumer differentiation. Compared to downward substitution, inducing bidirectional substitution through product line decisions including quality levels and prices can yield greater risk pooling effects. However, we show that the additional benefit from the risk pooling effect cannot compensate for the reduced market segmentation effect. We demonstrate that the presence of demand uncertainty can reduce the benefit of market segmentation and therefore the length of product lines in terms of the difference between products. We also propose three heuristics that separate product line and production decisions; each of these heuristics corresponds to one particular form of demand substitution. Our numerical studies indicate that the best of the three heuristics yields performance that is close to optimality. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 143–157, 2015

Modular product design, as part of a product family strategy, is a key methodology for mass customisation and significantly impacts production line configuration. Common modules shared across product families, generations, and the entire product platform have varying lifecycles due to constant changes in market demand. Therefore, it is crucial to design a production line that can quickly respond to product change requirements while maintaining flexibility in both product and process variants. The objective of this research is to develop a hybrid decision-making framework for determining an optimal production line configuration based on product modularity and lifecycle. In the proposed framework, three scenarios related to production line configuration are modelled as batch, mixed-model, and intermittent production lines based on specific product lifecycle. After modelling the three lines, data on processing times and inventory levels are gathered, while assumptions for additional data are made with industry collaborators. The proposed models are used as evaluation criteria in a Multi-Criteria Decision-Making (MCDM) framework to determine an optimal production line configuration by integrating product modules and lifecycle. The proposed research demonstrates the performance of the three scenarios quantitatively with eight sub-performance indicators, utilising a hybrid MCDM and real production line simulation data.

Product line design is a key decision area that a product development team has to deal with in the early stages of product development. Previous studies of product line design have focused on single-objective optimization. However, several optimization objectives may be simultaneously pursued, and the solutions that can address the objectives are required in many practical scenarios. In this research, we propose a one-step multiobjective optimization approach for product line design. The proposed optimization model has three objectives: 1) maximizing the market share of a company's products; 2) minimizing the total product development cost of a product line; and 3) minimizing the total product development cycle time. A curve-fitting method is introduced into the part-worth utility models so that the optimization model can be applied to products with level-based attributes and attributes that have continuous values. A multiobjective genetic algorithm is adopted to solve the optimization model, obtaining a set of nondominated solutions. With the solutions, a new product development team can select a preferred solution interactively in a 2-D graph. An example of the optimal design of a product line of digital cameras is used to illustrate the proposed approach.

In order to meet the requirements of automatic processing for mechanical components manufacturing enterprises, the paper describes a design method of automatic production line. Firstly, the paper made the overall design of the automatic production line, takt time is calculated according to the annual production demand, and the analysis of device configuration and position layout of the production line was carried out based on the annual production requirement. Secondly, the paper selects types of CNC machines and industrial robots, and design structural of the silo, the temporary storage platform, the conveyor belt, the fuel injection and water removal. 3D model of each component and space layout of the production line are drawn by Solidworks software. Thirdly, the process flow of automatic production line was designed, and the CNC intelligent management system was developed to meet the requirements, which can monitor the process information such as takt time. Test is carried out after establishment of automatic production line, the test run finally shows that the automatic production line works stably and can meet the requirements of enterprise.

A one-step multiobjective optimization model for product line design based on the conditional multi nominal logit choice rule is established. The two objectives of the proposed model are maximizing total the product demand in a multi-segment market and minimizing the total develop cost of a product line. The influence of the number of selected product profiles on the product development cost is considered in the model by introducing a cost reduction coefficient. Moreover, a curve fitting method is introduced into the part-worth utility model so that the optimization model can be applied to products with level-based attributes and attributes which have continuous values. A multiobjective genetic algorithm is developed to solve the proposed model and a set of non-dominated solutions can de achieved. With these non-dominated solutions, a firm manager can select a preferred solution interactively. An example of the optimal design of product line of digital cameras is used to illustrate the proposed model and algorithm.

The Maximal Profit Model for reaching an optimal design of the production line undergoing the limitations of obtainable resources is presented in this paper. This model is treated as an integer programming problem, and an efficient step-by-step algorithm to solve this problem is also constructed. In addition, it is discussed that the operation cost of a machine does not include idle and breakdown situations while the maintenance cost for a broken machine should be considered. This study offers a better tool for achieving the optimal design of a flexible production line and reveals the special applicability of the shortest path in production line design.

Researchers have expanded the definition of product modularity from function-based modularity to life-cycle process-based modularity. In parallel, measures of product modularity have been developed as well as corresponding modular product design methods. However, a correct modularity measure and modular design method are not enough to realize modular product design. To apply the measure and design method correctly, product representation becomes an important aspect of modular design and imperative for realizing the promised cost savings of modularity. In this paper, a representation for retirement process-based modular design has been developed. Built upon previous representations for assembly and manufacturing-based product design, the representation includes a process similarity matrix and a process dependency matrix. The retirement process-based similarity is based on the similarity in components’ post-life intents (recycling, reuse, disposal), and either the degree of their material compatibility if the components will be recycled, or their disassembly direction or disassembly tools if they need to be disassembled from each other for retirement. Process similarity within a module leads to increased process efficiency (the elimination of non-value added tasks) from the sharing of tooling/equipment. Retirement process-based dependency is developed based on disassembly difficulty, one aspect of the physical interactions between components. Retiring components together as a module to eliminate disassembly and differential processing and reducing the disassembly difficulty between the modules can increase the efficiency of the retirement process. We have first presented which process elements we should consider for defining retirement process similarity and dependency, and then constructed the respective similarity and dependency factors tables. These tables include similarity and dependency factors, which, along with their quantifications, are used to determine a product’s modular architecture to facilitate the retirement process. Finally, a fishing reel is used to illustrate how to apply these factors tables to generate the similarity and dependency matrices that represent a product for retirement-process based modular design. Using these representations as input to the DSM-based modular design methods, we can achieve a design with a modular architecture that improves the retirement process efficiency and reduces retirement costs.

For the development of variable systems, software product lines (SPL) are an established way to handle the variability by using feature models. Nevertheless, the configuration of an SPL can be complex, especially if a product line consists of a large number of features. The problem of handling the complexity becomes even more sophisticated if not only software, but also mechatronic systems containing software and hardware components are configured. Besides modeling the software, within a mechatronic system dependencies and associations between software and hardware features need to be considered which further increases the complexity. To handle this complexity in product lines for mechatronic systems, we propose a multi product line (MPL) approach which allows to distinguish between software and hardware by using different feature models for each. In addition we introduce a level of abstraction to complex product lines consisting of multiple feature models by establishing a feature model mapping. In this paper we present details to the mapping to provide an abstract configuration view as well as the introduced associations for our MPL approach.

In order to meet the requirements of solid dosage production process, modularity, stability and total quality management, a modular production line control system based on configuration principle is presented. The design and development of system is based on configuration principle, which mainly includes configuration software module and process generation module. And the configuration software module can change its own physical and logic configurations according to different production objects, and build a dedicated product-specific control system; the process generation module implements the automatic selection and optimization of process parameters of machining equipments using neural networks. The system design principle and structure are detailed in the paper, and the practical application example in the industrial field is also presented, whose results show that the proposed control system can effectively control modular pharmaceutical production line.

On the product line selection problem under attraction choice models of consumer behavior

This research was driven by the need for a more efficient production scheduling system in a consumable liquid product division of a large consumer products company. The manufacturing process under inspection consists of continuous and discrete elements, on both production and packaging lines. The production lines are split into continuous production lines and batch production lines which produce the product in fixed batch amounts. Then there are several bottling lines, some of which package a particular bottle size and others that can package multiple bottle sizes. The main objective of this research was to reduce the amount of time it takes for the client to create production and bottling schedules. An optimization model was developed to automate this process and provide the client with the best possible schedule. The objective of the model is to minimize cost by minimizing the number of switches across the production and bottling lines, as well as minimizing the amount of overproduction. Inputs into the model include model parameters, like the number of shifts to schedule, and monthly demand numbers for each stock keeping unit (SKU). The variables being solved for are the amount of each flavor to be produced across the production lines during each shift, and the number of bottles of each SKU to be bottled across the bottling lines during each shift. Due to the unique constraints and resources of the client, a custom formulation using mixed integer programming was necessary to achieve these objectives. Overall, our model fell short in some areas but succeeded in others. Our analysis showed that the model had a 13% average decrease in production switches but an 87% average increase in bottling switches compared to the current manual scheduling system. However, the ability of our system to create a good enough initial schedule reduces the time it takes expert human schedulers to develop a final schedule by up to 85%. Runtime and computational constraints barred us from creating an optimal, cost-minimized solution for our client, and future work can be directed toward solving these issues.

The article discusses the problems of modeling and simulation in the design of production lines, mainly from an educator's perspective. Nowadays, there is a wide range of computer programs that can be used to design production lines and to simulate various aspects of their operation. However, the programs being available vary considerably as to their functionality, the approach to production system design, and the visualization tools. Therefore we demonstrate and evaluate in this paper four simulation programs, focusing on the easiness of system design, area of the possible applications in education of engineers, and the limitations imposed by versions dedicated for students. We evaluate three of programs for digital factory simulation on a common, simple assembly task, then demonstrate that these programs may be also used for more specialized simulations in various areas of production, and compare with a specialized program for simulation of robotised production lines and work cells.

Large-scale software-intensive systems often consist of multiple heterogeneous and loosely coupled systems, which work together to form a system of systems (SoS). The individual systems often represent configurable units that need be adapted to customer requirements. In such multi product line environments, configuration dependencies between the product lines need to be discovered and enforced. Based on an analysis of the SoSs of our industry partners in the domains of medical systems and industrial automation, we identify several types of configuration dependencies between product lines. In particular, we point out the importance of emerging dependencies, which are not known in advance, but are detected in the course of the configuration process. For handling such emerging dependencies, we developed tool extensions to the DOPLER tool suite that provide support for the distributed configuration of multi product lines by multiple users and that support the inference of dependencies from emerging dependencies by observing user actions. We conducted a preliminary evaluation to assess our tool-supported approach. Our extensible set of dependency types turned out to be suitable for modeling configuration dependencies between product lines in the study system. The evaluation further showed the usefulness of the tool for capturing emerging dependencies by multiple users during distributed configuration.

This article discusses the development of a grapho-analytical method for modeling technological processes of discrete-continuous production lines of timber warehouses. The proposed approach is based on matrix transformations of coordinates and allows us to analytically describe the structure of technological operations with visualization in the form of graphs of displacement versus time. The authors have identified two key modeling methods: summation of displacement vectors and summation of particular time values, of which the first is more effective for longitudinal feeding of wood raw materials. The work focuses on the current problems of production line design, historically estab-lished methods, as well as the advantages of the grapho-analytical approach over traditional methods. The purpose of the research is to develop a structured method for modeling technological processes to improve the design and optimi-zation of production lines of timber warehouses. The research methods include theoretical modeling, analytical descrip-tion of processes based on matrix transformations and graphical representation of the results. Results: A new modeling method is proposed that makes it possible to simplify the process of designing warehouse infrastructure and increase its accuracy. The technique demonstrates its effectiveness in modeling the operation of longitudinal feed lines for wood raw materials. Scope of application: The developed approach is focused on use in the forestry industry, but it can be adapted to other industries with similar technological challenges. Conclusion: The presented modeling method makes it possible to optimize the design of production lines, reducing the time and financial costs of experimental development. The work has scientific and practical significance for the development of the concept of integrated use of forest re-sources. The work was carried out within the framework of the scientific school "Innovative developments in the field of logging industry and forestry".

The use of automated guided vehicles (AGVs) as transporters and mobile workstations in automated assembly lines is on the increase. This is due in part to the flexibility AGVs introduce in the design of production lines. In this paper, models for the management and control of material flow through AGV based production lines are developed. The use of the models permits the line designer to optimally determine the launch times of successive unit loads of parts into the line to minimize production makespan while balancing between line idleness and the idleness of vehicles employed on the line. The use of the models for AGV based production line design purposes is demonstrated through example problems.