https://bura.brunel.ac.uk/bitstream/2438/17829/4/FullText.pdf

Big data analytics in supply chain management: A state-of-the-art literature review

Mass production system design is a key for the productivity of an organization. Mass production system can be classified into production line machining a component and production line assembling a product. In this paper, the production line assembling a product, which is alternatively called as assembly line system, is considered. In this system, balancing the assembly line as per a desired volume of production per shift is a challenging task. The main objectives of the assembly line design are to minimize the number of workstations for a given cycle time (type 1), to minimize the maximum of the times of workstations for a given number of workstations (type 2), and so forth. Because this problem comes under combinatorial category, the use of heuristics is inevitable. Development of a mathematical model may also be attempted, which will help researchers to compare the solutions of the heuristics with that of the model. In this paper, an attempt is made to present a comprehensive review of literature on the assembly line balancing. The assembly line balancing problems are classified into eight types based on three parameters, viz. the number of models (single-model and multi-model), the nature of task times (deterministic and probabilistic), and the type of assembly line (straight-type and U-type). The review of literature is organized as per the above classification. Further, directions for future research are also presented.

Literature review of assembly line balancing problems

Traditionally, assembly lines are arranged in a straight line. The design of such a line requires tasks to be grouped into stations such that the line efficiency is maximized. This problem is known as the assembly line balancing problem. However, as a consequence of introducing the just-in-time production principle, it has been recognized that arranging the stations in a U-line has several advantages over the traditional configuration. For solving different versions of the U-line assembly line balancing problem, we propose the branch and bound procedure ULINO which is applied directly and in the framework of search methods. Experimental results indicate that these procedures perform well and that the U-line configuration frequently improves the line efficiency compared to traditional lines.

ULINO: optimally balancing U-shaped JIT assembly lines

The disassembly line balancing (DLB) problem assigns the set of tasks to each workstation for each product to be disassembled and aims at attaining several objectives, such as minimising the number...

https://hal.archives-ouvertes.fr/hal-02421246/document

Disassembly line balancing problem: a review of the state of the art and future directions

Performance measures and metrics (PMM) is identified to be an essential aspect of managing diverse supply chains. The PMM improves the firm’s performance by providing open and transparent communica...

Big data-driven supply chain performance measurement system: a review and framework for implementation

A heuristic approach for U-shaped assembly line balancing to improve labor productivity

Prioritization of aesthetic attributes of car profile

A company must purchase a lot of diverse components and raw material from different upstream suppliers to manufacture or assemble its products. Under this situation the supplier selection has become a critical issue for the purchasing department.The selection of suppliers depends on number of criteria and the challenge is to optimize selection process based on critical criteria and select the best supplier(s). During supplier selection process initial screening of potential suppliers from a large set is vital and the determination of prospective supplier is largely dependent on the criteria chosen of such pre-qualification. In the literature, many judgments based methods are proposed and derived criteria selection from the opinion of either the customers or the experts. All these techniques use the knowledge and experience of the decision makers. These methods inherit certain degree of uncertainty due to complex supply chain structure. The extraction of hidden knowledge is one of the most important tools to address such uncertainty and data mining is one such concept to account for such uncertainty and it has been found applicable in many scenarios. The proposed research aims to introduce a data mining approach, to discover the hidden relationships among the supplier's pre-qualification data with the overall supplier rating that have been derived after observation of previously executed work for a period of time. It provides an overview that how supplier's initial strength influence its final work performance.

Using data mining synergies for evaluating criteria at pre-qualification stage of supplier selection

Disassembly of discarded products takes place in the process of remanufacturing, recycling, and disposal. The disassembly lines have been taken as available choice for automated disassembly; therefore, it has become essential that it be designed and balanced to work efficiently. The multi-objective disassembly line balancing problem seeks to find a disassembly sequence which provides a feasible disassembly sequence, minimizes the number of workstations and idle time, and balances the line for the disassembly of post consumed product by considering the environment effects. This paper proposes a multi-criteria decision making technique based heuristic for assigning the disassembly tasks to the workstations. In the proposed heuristic, the PROMETHEE method is used for prioritizing the tasks to be assigned. The tasks are assigned to the disassembly workstations according to their priority rank and precedence relations. The proposed heuristic is illustrated with an example, and the results show that substantial improvement in the performance is achieved compared with other heuristics.

/pdf/a-promethee-method-based-heuristic-for-disassembly-line-4t19soqfzq.pdf

A PROMETHEE Method Based Heuristic for Disassembly Line Balancing Problem

Visual shape parameters and aesthetic aspects of a product are one of the decisive factors for the success of a product in the market. Since designers are responsible for the visual appearance of a product, they tend to be critical in their decisions concerning the type and the values of the shape parameters. Inclusion of aesthetic aspect in product design and development has been challenging task for the researchers. Fuzzy based approach has been appropriate methodology to convert the customer emotion into usable design data. This study presents an integrative design approach incorporating the fuzzy AHP, Taguchi method and grey relation analysis (GRA) to obtain the optimal combination of shape parameters and aesthetic aspects. The method has been illustrated to evolve a profile of car.

H. C. Yadav

Papers

A heuristic approach for U-shaped assembly line balancing to improve labor productivity

Prioritization of aesthetic attributes of car profile

Using data mining synergies for evaluating criteria at pre-qualification stage of supplier selection

A PROMETHEE Method Based Heuristic for Disassembly Line Balancing Problem

Robust design approach with fuzzy-AHP for product design to enhance aesthetic quality