Complex Product Structures Research Articles

Models for the Single Product Disassembly Lot Sizing Problem with Disposal

Abstract This paper considers a single product disassembly lot sizing problem with disposal decision (DLSPD) in order to reduce the costs as well as environmental impacts related to returned products. This is the problem of determining the quantity and time of the returned products to be disassembled while satisfying the demand of their parts or components over a planning horizon. Due to the existence of yield (in a disassembly system) and demand, which are not well balanced during planning horizon, surplus inventory of leaf items will be conducted. The integer programming (IP) can be used to arrive at optimal solution, with the disadvantage that the computational time explodes with increasingly complex product structure and larger size of problem. In this case, LP relaxation approach can be useful. Two integer programming models (aggregate formulation (AGG) and disaggregate formulation (FAL)) with considering disposal decision are developed to cope with the unnecessary surplus inventory. This paper focus on the problem with no capacity restriction on disassembly resource, and single product type with two-level product structure. The computation experiments are conducted to evaluate the performance of proposed models using CPLEX solver for different generated instance sizes. For large-sized problem, LP relaxation approach is suggested and compared with integer/optimal solution to show its effectiveness. The LP relaxation gives a strong lower bound (LB) for the proposed mixed-integer programming models.

An optimizing model for solving outsourcing supplier selecting problem based on particle swarm algorithm

ABSTRACTThe characteristics of decentralization, diversification, and dynamics of outsourcing resources put forward higher requirements for the supplier selection in manufacturing enterprises. For building materials equipment manufacturing enterprises (BMEM), due to the complex product structure, the demand for outsourcing resources is very large. The traditional method is difficult to meet the needs of current outsourcer evaluation and selection. In order to solve the problem, this paper establishes an outsourcing supplier selection model based on the quality, price, delivery time, reliability, and availability of outsourced suppliers. And then, a hybrid supplier selection algorithm based on Analytic Hierarchy Process (AHP) and Particle Swarm Optimization (PSO) is designed in this paper. Finally, the model and algorithm are verified and analyzed in BMEM. The paper also compares the algorithm with genetic algorithm (GA) and ant colony optimization (ACO). The experimental results show that the model can effectively improve the effectiveness and reliability of outsourcing supplier selection.

Becoming indispensable by using "Systems Thinking" to tackle challenging and complex problems in practice

Many veterinary practitioners and consultants play critical and indispensable roles in the management and decision-making processes of large, complex production structures. The discipline of Systems Thinking offers an opportunity and methodology to understand the interrelated forces that impact complex systems overtime in ways that help to identify innovative and high-leverage solutions. Systems Thinking is a dynamic tool that has long been used by business management entities to gain insight into effective and sustainable management strategies. This paper provides an introduction to the language and methodologies of Systems Thinking and how it can be applied to the veterinary profession in a way that allows us to understand and impact the challenging and complex problems inherent to livestock production.

A Hybrid Discrete Bat Algorithm with Krill Herd-based advanced planning and scheduling tool for the capital goods industry

Capital goods companies produce high value products such as power plant or ships, which have deep and complex product structures, with components having long process routings. Contracts usually include substantial penalties for late delivery. The high value of items can lead to substantial holding costs. Efficient schedules minimise earliness and tardiness costs and need to satisfy assembly and operation precedence constraints as well as finite capacity. This paper presents the first advanced planning and scheduling (APS) tool for the capital goods industry that uses a Discrete Bat Algorithm (DBA), modified DBA (MDBA) and hybrid DBA with Krill Herd algorithm (HDBK) to optimise schedules. The tool was validated using four data-sets obtained from a collaborating capital goods company. A sequential experimental strategy was adopted. The first experiment identified appropriate parameter settings for the DBA. The second experiment evaluated and compared the performance of the proposed HDBK algorithm with an Artificial Bee Colony, Krill Herd (KH), Modified KH, DBA and MDBA metaheuristics. The experimental results revealed that the HDBK performed best in terms of the minimum penalty cost for all problem sizes and achieved up to a 47.837% reduction in mean total penalty costs of extra-large problem size.

Symplectic, product and complex structures on 3-Lie algebras

In this paper, first we introduce the notion of a phase space of a 3-Lie algebra and show that a 3-Lie algebra has a phase space if and only if it is sub-adjacent to a 3-pre-Lie algebra. Then we introduce the notion of a product structure on a 3-Lie algebra using the Nijenhuis condition as the integrability condition. A 3-Lie algebra enjoys a product structure if and only if it is the direct sum (as vector spaces) of two subalgebras. We find that there are four types special integrability conditions, and each of them gives rise to a special decomposition of the original 3-Lie algebra. They are also related to O-operators, Rota–Baxter operators and matched pairs of 3-Lie algebras. Parallelly, we introduce the notion of a complex structure on a 3-Lie algebra and there are also four types special integrability conditions. Finally, we add compatibility conditions between a complex structure and a product structure, between a symplectic structure and a paracomplex structure, between a symplectic structure and a complex structure, to introduce the notions of a complex product structure, a para-Kähler structure and a pseudo-Kähler structure on a 3-Lie algebra. We use 3-pre-Lie algebras to construct these structures. Furthermore, a Levi-Civita product is introduced associated to a pseudo-Riemannian 3-Lie algebra and deeply studied.

A mixed-integer linear programming model for integrated production and preventive maintenance scheduling in the capital goods industry

The scheduling literature is extensive, but much of this work is theoretical and does not capture the complexity of real world systems. Capital goods companies produce products with deep and complex product structures, each of which requires the coordination of jobbing, batch, flow and assembly processes. Many components require numerous operations on multiple machines. Integrated scheduling problems simultaneously consider two or more simultaneous decisions. Previous production scheduling research in the capital goods industry has neglected maintenance scheduling and used metaheuristics with stochastic search that cannot guarantee an optimal solution. This paper presents a novel mixed integer linear programming model for simultaneously solving the integrated production and preventive maintenance scheduling problem in the capital goods industry, which was tested using data from a collaborating company. The objective was to minimise total costs including: tardiness and earliness penalty costs; component and assembly holding costs; preventive maintenance costs; and set-up, production, transfer and production idle time costs. Thus, the objective function and problem formulation were more extensive than previous research. The tool was successfully tested using data obtained from a collaborating company. It was found that the company’s total cost could be reduced by up to 63.5%.

COMPLEX PRODUCT STRUCTURES ON HOM-LIE ALGEBRAS

AbstractIn this paper, we introduce the notion of complex product structures on hom-Lie algebras and show that a hom-Lie algebra carrying a complex product structure is a double hom-Lie algebra and it is also endowed with a hom-left symmetric product. Moreover, we show that a complex product structure on a hom-Lie algebra determines uniquely a left symmetric product such that the complex and the product structures are invariant with respect to it. Finally, we introduce the notion of hyper-para-Kähler hom-Lie algebras and we present an example of hyper-para-Kähler hom-Lie algebras.

Pd‐Catalyzed versus Uncatalyzed, PhI(OAc)2‐Mediated Cyclization Reactions of N6‐([1,1′‐Biaryl]‐2‐yl)Adenine Nucleosides

AbstractThe front cover artwork for Issue 21/2017 is provided by the Lakshman Group at The City College of New York (USA). The image shows the beautifully delicate architecture of Hawa Mahal, in Jaipur, as a symbol of the delicate balance of various factors in the described C−N bond formation of N6‐([1,1′‐biaryl]‐2‐yl)adenine nucleosides promoted by PhI(OAc)2 under both Pd‐mediated and uncatalyzed reaction conditions, which ultimately leads to relatively complex product structures. See the Full Paper itself at https://doi.org/10.1002/cctc.201700918.

A Research on the Applications of Supply Chain in Textile-Clothing Industry

Nowadays most of the firms understood the importance of obtaining competitive advantage of inter- enterprise relations and started to re-establish the relations of both suppliers and customers depending on basis of mutual cooperation and gain. Especially developing close coordination with suppliers is seen to provide quite positive contributions to the areas like increasing product quality, decreasing the cost of purchased products, developing the production and logistic flexibility, increasing customer satisfaction. Constantly changing fashion, various shopping seasons, different materials, various accessories are the features which affect the process in textile industry. Besides constant increasing competition, price pressure, shortening the process of supply of products into markets, import/export, complex production structures, working with third parties are operation a factors which describe the structure of textile industry. This study was prepared with the aim of determining the applications of supply chain of textile-clothing industry. The study was applied on 497 active textile-clothing firms which affiliated with TOBB (Union of Chambers and Commodity Exchanges of Turkey) in the last quarter of 2012. In this study supply chain applications were analysed in textile-clothing industry. Consequently in textile-clothing industry some variables have been reached in relation to supply chain applications.

Computational path planner for product assembly in complex environments

Assembly path planning is a crucial problem in assembly related design and manufacturing processes. Sampling based motion planning algorithms are used for computational assembly path planning. However, the performance of such algorithms may degrade much in environments with complex product structure, narrow passages or other challenging scenarios. A computational path planner for automatic assembly path planning in complex 3D environments is presented. The global planning process is divided into three phases based on the environment and specific algorithms are proposed and utilized in each phase to solve the challenging issues. A novel ray test based stochastic collision detection method is proposed to evaluate the intersection between two polyhedral objects. This method avoids fake collisions in conventional methods and degrades the geometric constraint when a part has to be removed with surface contact with other parts. A refined history based rapidly-exploring random tree (RRT) algorithm which bias the growth of the tree based on its planning history is proposed and employed in the planning phase where the path is simple but the space is highly constrained. A novel adaptive RRT algorithm is developed for the path planning problem with challenging scenarios and uncertain environment. With extending values assigned on each tree node and extending schemes applied, the tree can adapts its growth to explore complex environments more efficiently. Experiments on the key algorithms are carried out and comparisons are made between the conventional path planning algorithms and the presented ones. The comparing results show that based on the proposed algorithms, the path planner can compute assembly path in challenging complex environments more efficiently and with higher success. This research provides the references to the study of computational assembly path planning under complex environments.

The performance of Due Date setting rules in assembly and multi-stage job shops: an assessment by simulation

Setting short yet reliable Due Dates (DDs) is an important early production planning and control task. The majority of job-shop research on DD setting assumes simple product structures without assembly operations. However, in practice, product structures are often complex, and multiple final assembly operations may be required. This paper evaluates the performance of DD setting rules in the context of complex product structures, considering two scenarios: two-level assembly job shops, where orders converge on one final assembly operation; and two-level multi-stage job shops, where a series of assembly operations are undertaken. New rules are proposed which are substantially simpler and more suitable for practical use than those in the literature. These rules are only outperformed by a more sophisticated rule from the wider literature, newly introduced into the context of assembly and multi-stage job shops. Which rule to apply in practice depends on whether a manager considers the improvement in performance more important than the loss of simplicity. Future research should investigate how jobs can be planned and controlled effectively when some or all DDs are set externally by customers rather than internally using a DD setting rule.

Digital Innovation and the Division of Innovative Labor: Digital Controls in the Automotive Industry

In this study of the U.S. automobile industry, we highlight the way the division of innovative labor across firms in the supply chain can be influenced by a particular form of digital innovation known as “digital control systems.” Digital control systems are becoming ubiquitous in complex products, and these digital innovations integrate other components across a product structure and introduce a level of indeterminacy and unpredictability in the organization of the interfirm division of innovative labor. Much of organizational scholarship holds that accompanying a shift toward increasingly modular product structures, component suppliers are engaging in relatively more design and invention around the components that they supply. We find that the evolution of digital controls may reverse this pattern, because in the wake of a major shift in the digital controls technology, suppliers actually engage in relatively less component innovation in comparison with their large manufacturing customers. To explain this shift, we characterize complex product structures in terms of two distinct product hierarchies: the inclusionary and the digital control hierarchy. In using this distinction to analyze the evolution of automotive emission control systems from 1970 to 1998, we reconcile two competing views about the interfirm division of innovative labor.

A New Dynamic Version Control Method Oriented the Complex Product

There are a lot of dynamic changing problems for design version in the complex product design process. We have study a dynamic version control technology for result it. Firstly, we have researched the three level version control model, including the complex product structure layer, the node version tree layer and the version structure layer. Secondly, we have researched the version control model operations, including the version structure operations and the version operations, and analyzed the implementation of the version generation function and the version mergence function. Finally, the method has been applied and verified in the development of an aircraft flight loads integrated design platform.

The Application of Particle Swarm Optimization Algorithm in the Production Scheduling Modeling of ERP-Based

Job shop scheduling in the production management module is one of the core of ERP system. To solve the problem, that is, to discretely manufacture the multi-process routes and the multi-objective job shop scheduling, this paper propose an optimized algorithm of the improved particle swarm that is used to establish the mathematical model which turns in the direction of the production scheduling system of ERP-based. And with the example of an engineering machinery manufacturing enterprise, it deduces a model’s realization process in the multi-objective shop scheduling in the discrete manufacturing of more complex product structures. It finally gives integration framework of production scheduling system based on the real-time capacity balance, which are based on the particle swarm optimization (PSO) algorithm, and together with the other modules of ERP system. It provides an important practical value for discrete manufacturing enterprises using ERP system to realize scientific and effective production operation management.

Enhanced control of complex production structures by tight coupling of the digital and the physical worlds

Unexpected disturbances and local decisions almost always deteriorate the execution of manufacturing plans. Digital enterprise technologies are hard to use, due to the complexity of production and the frequently changing circumstances. One of the main goals of the research described in the paper is the automatic model building of the discrete-event simulation system, based on intelligent analysis of the huge amount of information incorporated in the production database. The developed solution supports shop-floor dispatching and shop-floor managers in making control decisions.

Modeling complex longitudinal consumer behavior with Dynamic Bayesian networks: an Acquisition Pattern Analysis application

Longitudinal consumer behavior has been modeled by sequence analysis. A popular application involves Acquisition Pattern Analysis exploiting typical acquisition patterns to predict a customer's next purchase. Typically, the acquisition process is represented by an extensional, unidimensional sequence taking values from a symbolic alphabet. Given complex product structures, the extensional state representation rapidly evokes the state-space explosion problem. Consequently, most authors simplify the decision problem to the prediction of acquisitions for selected products or within product categories. This paper advocates the use of intensional state definitions representing the state by a set of variables thereby exploiting structure and allowing to model complex, possibly coupled sequential phenomena. The advantages of this intensional state space representation are demonstrated on a financial-services cross-sell application. A Dynamic Bayesian Network (DBN) models longitudinal customer behavior as represented by acquisition, product ownership and covariate variables. The DBN provides insight in the longitudinal interaction between a household's portfolio maintenance behavior and acquisition behavior. Moreover, it exhibits adequate predictive performance to support the financial-services provider's cross-sell strategy comparable to decision trees but superior to MulltiLayer Perceptron neural networks.

Current state and potential of variability management practices in software-intensive SMEs: Results from a regional industrial survey

Context More and more, small and medium-sized enterprises (SMEs) are using software to augment the functionality of their products and offerings. Variability management of software is becoming an interesting topic for SMEs with expanding portfolios and increasingly complex product structures. While the use of software product lines to resolve high variability is well known in larger organizations, there is less known about the practices in SMEs. Objective This paper presents results from a survey of software developing SMEs. The purpose of the paper is to provide a snapshot of the current awareness and practices of variability modeling in organizations that are developing software with the constraints present in SMEs. Method A survey with questions regarding the variability practices was distributed to software developing organizations in a region of Sweden that has many SMEs. The response rate was 13% and 25 responses are used in this analysis. Results We find that, although there are SMEs that develop implicit software product lines and have relatively sophisticated variability structures for their solution space, the structures of the problem space and the product space have room for improvement. Conclusions The answers in the survey indicate that SMEs are in situations where they can benefit from more structured variability management, but the awareness need to be raised. Even though the problem space similarity is high, there is little reuse and traceability activities performed. The existence of SMEs with qualified variability management and product line practices indicates that small organizations are capable to apply such practices.

Complex product structures on 6-dimensional nilpotent Lie algebras

We study complex product structures on nilpotent Lie algebras, establishing some of their main properties, and then we restrict ourselves to 6 dimensions, obtaining the classification of 6-dimensional nilpotent Lie algebras admitting such structures. A study is made of the torsion-free connection associated to the complex product structure, and we consider also the associated foliations on the corresponding simply connected nilpotent Lie groups.

Dynamic scheduling for complex engineer-to-order products

The current paper considers dynamic production scheduling for manufacturing systems producing products with deep and complex product structures and complicated process routings. It is assumed that manufacturing and assembly processing times are deterministic. Dynamic scheduling problems may be either incremental (where the schedule for incoming orders does not affect the schedule for existing orders) or regenerative (where a new schedule is produced for both new and existing orders). In both situations, a common objective is to minimize total costs (the sum of work-in-progress holding costs, product earliness and tardiness costs). In this research, heuristic and evolutionary-strategy-based methods have been developed to solve incremental and regenerative scheduling problems. Case studies using industrial data from a company that produces complex products in low volume demonstrate the effectiveness of the methods. Evolution strategy (ES) provides better results than the heuristic method, but this is at the expense of significantly longer computation times. It was found that performing regenerative planning is better than incremental planning when there is high interaction between the new orders and the existing orders.

Raw material release time control for complex make-to-order products with stochastic processing times

This paper considers a make-to-order manufacturing system producing complex products with multiple resource constraints, multiple levels of product structures, and stochastic processing times. The objective is to find the optimal raw material release times by minimising the expected sum of work-in-progress holding costs, product earliness costs and product tardiness costs. An evolution strategy-based planning tool is developed, in which the performance measure is evaluated by stochastic discrete event simulation. The tool is applied to an illustrative example that includes wide, deep and complex product structures and to a case study using data obtained from an industrial company that manufactures capital goods. It is demonstrated that the solutions produced perform substantially better than those produced by the backward scheduling based on infinite capacity, and also significantly better than those produced by the same search method based on deterministic processing times. More benefit can be achieved if the system has a higher degree of uncertainty.