An Investigation of Impact of the Product Family Design on the Shop Floor Performance

Author(s):  
Hakan U. Artar ◽  
Gu¨l Okudan

While many approaches have been proposed to optimize the product family design for measures of cost, revenue and performance, many of these approaches fail to incorporate the complexity of the manufacturing issues into family design decision-making. One of these issues is different approaches for assembly sequencing. This paper presents a computer simulation study by which the impact of two postponement strategies is investigated for a real-life product family case under various demand conditions. Overall, the results indicate that when the product family design takes into account the assembly sequencing decisions, the outcomes at the shop floor level improve. The results have implications for companies that are looking into increasing their revenue without increasing their investment in the shop floor.

Author(s):  
Shafin Tauhid ◽  
Hakan U. Artar ◽  
Saraj Gupta ◽  
Gu¨l Okudan

While many approaches have been proposed to optimize the product family design for measures of cost, revenue and performance, many of these approaches fail to incorporate the complexity of the manufacturing issues into family design decision-making. One of these issues is assembly sequencing. This paper presents a simulation study by which the impact of assembly sequencing on the product family design outcomes is investigated. Overall, the results indicate that when the product family design takes into account the assembly sequencing decisions, the outcomes at the shop floor level improve. The results have implications for companies that are looking into increasing their revenue without increasing their investment in the shop floor.


2012 ◽  
Vol 3 (3) ◽  
pp. 47-56
Author(s):  
Kashif Nisar ◽  
Nurul I. Sarkar

The Advanced Network Technologies is a research that investigates the technology(s) behind today’s modern networks and network infrastructures one of these technologies being Asynchronous Transfer Mode (ATM). Therefore, also focuses its attention on ATM. Dubbed “Modelling and Performance Studies of ATM Networks”; this research seeks to look at, and into, the impact of application segment length on the performance of an ATM network and the impact of traffic type data on the performance of an ATM network. To be able to examine an ATM network, we need to be able to simulate it somehow. This research, the authors have used the OPNET Modeler 14.0 simulation tool to create a network model that represents a real-life ATM network. And by actually simulating an ATM network at AUT University New Zealand, they can therefore change certain variables, and observe the effects the changes have on performance. As stated above, one of the impacts that will be explored is the effect that application segment length has on an ATM network. Thus, one variable that will be changed in our simulation is the segment length. This is the length of each packet segment that is sent through the network for a particular traffic type. The second impact to be inspected is the impact of different traffic types on an ATM network. For example, voice & video traffic should theoretically affect an ATM network


2012 ◽  
Vol 40 (3) ◽  
pp. 381-394 ◽  
Author(s):  
Huey-Wen Chou ◽  
Yu-Hsun Lin ◽  
Shyan-Bin Chou

With the growing use of teamwork for strategic decision making in organizations, an understanding of the teamwork dynamics in the strategic decision-making process is critical for both researchers and practitioners. By conceptualizing team cognition in terms of a transactive memory system (TMS) and collective mind, in this study we explored the relationships among TMS, collective mind, and collective efficacy and the impact of these variables on team performance. Longitudinal data collected from 98 undergraduates were analyzed. Neither the TMS–team performance relationship nor the collective mind–team performance relationship was significant. Collective efficacy was found to play a mediating role in such relationships. We concluded that team cognition with collective efficacy is beneficial for understanding teamwork dynamics in strategic decision making.


2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Chenlu Miao ◽  
Gang Du ◽  
Yi Xia ◽  
Danping Wang

Many leader-follower relationships exist in product family design engineering problems. We use bilevel programming (BLP) to reflect the leader-follower relationship and describe such problems. Product family design problems have unique characteristics; thus, mixed integer nonlinear BLP (MINLBLP), which has both continuous and discrete variables and multiple independent lower-level problems, is widely used in product family optimization. However, BLP is difficult in theory and is an NP-hard problem. Consequently, using traditional methods to solve such problems is difficult. Genetic algorithms (GAs) have great value in solving BLP problems, and many studies have designed GAs to solve BLP problems; however, such GAs are typically designed for special cases that do not involve MINLBLP with one or multiple followers. Therefore, we propose a bilevel GA to solve these particular MINLBLP problems, which are widely used in product family problems. We give numerical examples to demonstrate the effectiveness of the proposed algorithm. In addition, a reducer family case study is examined to demonstrate practical applications of the proposed BLGA.


2018 ◽  
Vol 13 (6) ◽  
pp. 701-708 ◽  
Author(s):  
Marco J. Konings ◽  
Florentina J. Hettinga

Purpose: In real-life competitive situations, athletes are required to continuously make decisions about how and when to invest their available energy resources. This study attempted to identify how different competitive environments invite elite short-track speed skaters to modify their pacing behavior during head-to-head competition. Methods: Lap times of elite 500-, 1000- and 1500-m short-track speed skating competitions between 2011 and 2016 (N = 34,095 races) were collected. Log-transformed lap and finishing times were analyzed with mixed linear models. The fixed effects in the model were sex, season, stage of competition, start position, competition importance, event number per tournament, number of competitors per race, altitude, and time qualification. The random effects of the model were athlete identity and the residual (within-athlete race-to-race variation). Separate analyses were performed for each event. Results: Several competitive environments, such as the number of competitors in a race (a higher number of competitors evoked most likely a faster initial pace; coefficient of variation [CV] = 1.9–9.3%), the stage of competition (likely to most likely, a slower initial pace was demonstrated in finals; CV = −1.4% to 2.0%), the possibility of time qualification (most likely a faster initial pace; CV = 2.6–5.0%), and competition importance (most likely faster races at the Olympics; CV = 1.3–3.5%), altered the pacing decisions of elite skaters in 1000- and 1500-m events. Stage of competition and start position affected 500-m pacing behavior. Conclusions: As demonstrated in this study, different competitive environments evoked modifications in pacing behavior, in particular in the initial phase of the race, emphasizing the importance of athlete–environment interactions, especially during head-to-head competitions.


Author(s):  
Zhengqian Jiang ◽  
Hui Wang

Increased demand on product variety entails a flexible assembly system for product families which can be quickly configured and reconfigured in a responsive manner to deal with various product designs. Development of such a responsive assembly system requires an in-depth understanding of the impact of product family design on assembly system performance. In this paper, the linkage between the product family design and assembly systems is characterized by an assembly hierarchy model, which reflects a hierarchical relationship among all possible sub-assemblies and components, assembly tasks, and material flow among the tasks. Our prior research developed a recursive algorithm to generate all assembly hierarchy candidates for one single product based on its liaison graph without redundancy. These generated assembly hierarchies provide a structure to help efficiently explore optimal assembly system designs with reduced computational load. In this paper, the application of the assembly hierarchy generation algorithm will be extended to a product family by developing joint liaison graph model. Taking the advantage of the modular design of the product family, we proposed a concept of multi-level joint liaison graphs to overcome the computational challenge brought by assembly hierarchy generation for joint liaisons. Two case studies were conducted to demonstrate the algorithm.


2021 ◽  
Author(s):  
Ilya Kovalenko ◽  
Efe Balta ◽  
Dawn Tilbury ◽  
Kira Barton

Due to the advancements in manufacturing system technology and the ever-increasing demand for personalized products, there is a growing desire to improve the flexibility of manufacturing systems. Multi-agent control is one strategy that has been proposed to address this challenge. The multi-agent control strategy relies on the decision making and cooperation of a number of intelligent software agents to control and coordinate various components on the shop floor. One of the most important agents for this control strategy is the product agent, which is the decision maker for a single part in the manufacturing system. To improve the flexibility and adaptability of the product agent and its control strategy, this work proposes a direct and active cooperation framework for the product agent. The directly and actively cooperating product agent can identify and actively negotiate scheduling constraints with other agents in the system. A new modeling formalism, based on priced timed automata, and an optimization-based decision making strategy are proposed as part of the framework. Two simulation case studies showcase how direct and active cooperation can be used to improve the flexibility and performance of manufacturing systems.


2021 ◽  
Author(s):  
Ilya Kovalenko ◽  
Efe Balta ◽  
Dawn Tilbury ◽  
Kira Barton

Due to the advancements in manufacturing system technology and the ever-increasing demand for personalized products, there is a growing desire to improve the flexibility of manufacturing systems. Multi-agent control is one strategy that has been proposed to address this challenge. The multi-agent control strategy relies on the decision making and cooperation of a number of intelligent software agents to control and coordinate various components on the shop floor. One of the most important agents for this control strategy is the product agent, which is the decision maker for a single part in the manufacturing system. To improve the flexibility and adaptability of the product agent and its control strategy, this work proposes a direct and active cooperation framework for the product agent. The directly and actively cooperating product agent can identify and actively negotiate scheduling constraints with other agents in the system. A new modeling formalism, based on priced timed automata, and an optimization-based decision making strategy are proposed as part of the framework. Two simulation case studies showcase how direct and active cooperation can be used to improve the flexibility and performance of manufacturing systems.


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