Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Rahul Caprihan is active.

Publication


Featured researches published by Rahul Caprihan.


International Journal of Flexible Manufacturing Systems | 1997

Impact of Routing Flexibility on the Performance of an FMS—A Simulation Study

Rahul Caprihan; Subhash Wadhwa

The evolving manufacturing environment is characterized by a drive toward increasing flexibility. One possible manifestation of flexibility within an FMS is in the form of routing flexibility. Providing this typically is an expensive proposition, and system designers therefore aim to provide only the required levels commensurate with a given set of operating conditions. This paper presents a framework based on a Taguchi experimental design for studying the nature of the impact of varying levels of routing flexibility on the performance of an FMS. Simulation results indicate that increases in routing flexibility, when made available at the cost of an associated penalty on operation processing time, is not always beneficial. There is an optimal flexibility level, beyond which system performance deteriorates, as judged by the makespan measure of performance. It is suggested that the proposed methodology can be used in practice for not only setting priorities on specific design and control factors but also for highlighting likely factor level combinations that could yield near-optimal shop performance.


International Journal of Production Research | 2008

Least in-sequence probability heuristic for mixed-volume production lines

Oleg Gusikhin; Rahul Caprihan; Kathryn E. Stecke

The paper focuses on the sequencing aspects of a stochastic hybrid flexible assembly system (FAS) operating in a build-to-order environment. In such a system, although the flow of parts is unidirectional, parallel paths can exist for accommodating different types of parts produced and potential rework of the parts that fail inspection at a given production stage. As a result, the original sequential order of parts can become distorted, resulting in an exit demand sequence which is at variance with the input sequence. To compensate for such sequence disturbances, an adequately sized buffer is installed at the exit end of the FAS. From a practical viewpoint, the study is relevant to the sequencing of upstream operations in an automotive assembly plant functioning in an in-line vehicle sequencing mode. An important feature of the FAS considered in this study is that the demand sequence of part types is known and fixed for a given period of time. Further, the different part types that constitute the demand sequence can have different frequencies of occurrence in a range specified from low to high. We exploit this property of the demand sequence in the development of the least in-sequence probability (LISP) algorithm. The development of LISP is based on the trade-off of pulling low-volume parts ahead in the input sequence while delaying the high-volume parts. We propose the use of the heuristic as a means to achieve both of the following: (a) to improve customer service levels in terms of the number of in-sequence parts output from the system, given a fixed size for the re-sequencing buffers; and (b) to reduce re-sequencing buffer sizes given target levels of customer service.


International Journal of Production Research | 1997

Fuzzy systems for control of flexible machines operating under information delays

Rahul Caprihan; S. Kumar; Subhash Wadhwa

The performance of a manufacturing system with a defined level of flexibility is determined by the effectiveness of the control strategy employed. The success of the latter is critically dependent upon information intensive activities including information collection, transfer and processing. Each of these activities consumes time and thus causes delays. We refer to these delays as information delays. Most real-world manufacturing systems operate under conditions that entail significant information delays. Thus, there is a need to model, analyse and evolve control strategies that can perform well under such delays. This paper focuses on the design of a suitable control strategy for a simple system operating in a stochastic environment with information delays. System stochasticity coupled with information delay has a compounding effect on the uncertainty of the environment within which decisions must be taken thus providing motivation to explore the development of control strategies based on fuzzy logic. W...


Computers & Industrial Engineering | 1997

Performance of a hysteresis based control strategy for a flexible machine operating under a periodic status monitoring policy

Subhash Wadhwa; Rahul Caprihan; Satish Kumar

Abstract The role of on-line control strategies is crucial for exploiting the flexibility within discrete part manufacturing systems. When studying their impact on system performance, researchers have mostly assumed the presence of real-time information availability. Such assumption may not always be valid in real world manufacturing situations since on-line control strategies base their decisions on information that may entail significant time delays depending upon the extent of computer based automation and information integration employed. We refer to these delays as information delays . In the domain of discrete part manufacturing systems with defined levels of flexibility, it is essential explicitly to model and analyze the effect that information delays have on the performance of a given on-line control strategy. In this paper we conceptualize three basic modes of information delays and indicate the need to model them explicitly in order to assess their impact on the performance of on-line control strategies. One of these basic forms of information delay is caused due to a review period based status monitoring policy. We propose and characterize a hysteresis based on-line control strategy (HCS) to cope with information delays. The study system chosen represents the simplest possible manifestation of machine flexibility and resembles the two-queue single server case for which prior research results indicate the superiority of the alternating priority (AP) rule when average job flowtime is the measure of performance. We use computer simulation to compare the behaviour of HCS with the AP rule in a real-time as well as the information delay mode . The best HCS setting in the real-time mode fails to remain consistent in the information delay case, thus clearly indicating the need to explicitly model delays when developing suitable control strategies. Further, when compared with the AP rule, HCS shows consistently superior performance to AP.


Journal of Advances in Management Research | 2011

A case study on redesign of supply chain network of a manufacturing organization

Navin K. Dev; Rahul Caprihan; Sanjeev Swami

Purpose – The purpose of this paper is to analyze the case of a manufacturing firm situated in an industrial city of India, focusing on supply chain management issues of the concerned organization from two operational perspectives: supply side (or the procurement side) and the distribution side of the system.Design/methodology/approach – The authors first considered the outsourcing decision‐making problem in a static environment using analytical expression by means of a variable fraction of demand. Next, the authors extended the scope of this problem by considering outsourcing decisions in a dynamic environment, using the sequential decision‐making approach with various operational and inventory factors. Finally, the authors carried out the study of the distribution side of the supply chain of industry using discrete event simulation.Findings – It was observed that, in the case study organization, because of the rather unstructured approach in dealing with the outsourcing perspective, the authors suggeste...


International Journal of Information Systems and Supply Chain Management | 2013

Impact of Information Sharing in Alternative Supply Chain Network Structures

Navin K. Dev; Rahul Caprihan; Sanjeev Swami

Given the inherent uncertainties pervading the operational environment within real-world supply chains, it becomes imperative for each partnering echelon to focus on individual information requirements from the viewpoint of global optimization of overall supply chain SC performance. With this in perspective, it is expedient to explicitly model the SC network to synchronize activities across the cooperating partners. This research is concerned with the performance behaviour of two different SC network structures given different design and control parameters adopted by the partnering echelons within the assumed SC configurations. Accordingly, the authors developed discrete event simulation models of two hypothetical supply chain structures and exploit the Taguchi experimental design procedure as a vehicle for conducting the simulation experiments and analyzing its outcome. The results highlight the relative effects of the assumed design and controlling factors on system-wide SC performance and identify appropriate combinations of these factors for optimal performance concerned. For the average inventory level performance measure, key results reveal that sharing of demand information between partnering echelons should not automatically be taken for granted as a direction for performance enhancement.


Journal of Advances in Management Research | 2010

A discrete dynamic programming approach towards optimal outsourcing policy in supply chain management

Navin K. Dev; Sanjeev Swami; Rahul Caprihan

Purpose – As global markets become more customer oriented, rapid response rates are now often among the most important metrics in business. To achieve the required agility, many companies are forced to take decisions of whether to vertically integrate a value chain or to outsource some of its operations. The purpose of this paper is to develop a sequential decision modeling process to enable determination of optimal outsourcing policy decisions with respect to the variables such as warehouse inventory, in‐house manufacturing capacity and the ordering cost to the outsource supplier.Design/methodology/approach – In this paper, a discrete dynamic programming‐based modeling framework is developed for analyzing outsourcing policies for supply chain management problems. Specifically, the assumed situation entails a dynamic decision between in‐house production vis‐a‐vis outsourcing, which is contingent upon several factors such as demand during the period under consideration, available inventory, available produ...


industrial engineering and engineering management | 2009

A quantum particle swarm optimization approach for the design of virtual manufacturing cells

Rahul Caprihan; Jannes Slomp; Gursaran; Khushboo Agarwal

In this paper a QPSO procedure is proposed for the design of virtual manufacturing cells within which machines and jobs are assigned to the cells with a view to maximize productive output, whilst simultaneously minimizing the inter-cell movements due to the limited availability of machines. The QPSO results are compared with both a GA approach as well as a preemptive / lexico goal programming approach. It is observed that the suggested procedure performs well for the assumed VCM design problem.


International Journal of Logistics-research and Applications | 2013

Strategic positioning of inventory review policies in alternative supply chain networks: an information-sharing paradigm perspective

Navin K. Dev; Rahul Caprihan; Sanjeev Swami

One of the key issues in the current research on supply chain (SC) networks is the need for planning the nature of the inventory policy at each echelon of the SC network structure. Given the inherent uncertainties pervading the operational environment within real-world SC networks, it becomes imperative therefore, for each partnering echelon to focus on its individual inventory review policy from the viewpoint of global optimisation of the overall SC performance. Two key factors contributing to the aforementioned uncertainty are the lead time and their standard deviations, and the extant literature has often advocated the adoption of demand information-sharing between the partnering echelons to mitigate the deleterious impact of these factors on system performance. In this paper, we explicitly focus attention on these factors through their manifestation within two different hypothetical SC networks, and study their impact on the average fill rate performance of the assumed systems with and without demand information-sharing. Towards this end, we develop discrete event simulation models of the hypothetical SC structures and exploit the Taguchi experimental design procedure as a vehicle for conducting the simulation experiments and analysing its outcome. While simulation results highlight the impact of the assumed factors on system-wide performance, the Taguchi paradigm further helps identify appropriate combinations of these factors for optimal fill rate performance. Key results reveal that sharing of demand information between partnering echelons should not automatically be taken for granted as a direction for performance enhancement.


International Journal of Manufacturing Technology and Management | 2009

A modelling approach for outsourcing decisions in Supply Chain Management

Navin K. Dev; Sanjeev Swami; Rahul Caprihan

The rapidly changing global market scenario is increasingly forcing manufacturing firms to pursue outsourcing as an important option. From a research viewpoint, one issue that has remained relatively unexplored is the effect that capacity expansion with availability of overtime option and upstream supplier cost structure has on outsourcing decisions. There is scant research exploring the circumstances in which mixed models (fraction of demand) might be appropriate (Harland et al., 2005). The suggested model explicitly considers pricing and outsourcing simultaneously by operationalising the outsourcing decision through a variable that captures the fraction of demand met by in-house manufacturing through overtime.

Collaboration


Dive into the Rahul Caprihan's collaboration.

Top Co-Authors

Avatar

Jannes Slomp

University of Groningen

View shared research outputs
Top Co-Authors

Avatar

Navin K. Dev

Dayalbagh Educational Institute

View shared research outputs
Top Co-Authors

Avatar

Sanjeev Swami

Dayalbagh Educational Institute

View shared research outputs
Top Co-Authors

Avatar

Jos Bokhorst

University of Groningen

View shared research outputs
Top Co-Authors

Avatar

Khushboo Agarwal

Dayalbagh Educational Institute

View shared research outputs
Top Co-Authors

Avatar

Satish Kumar

Dayalbagh Educational Institute

View shared research outputs
Top Co-Authors

Avatar

Kathryn E. Stecke

University of Texas at Dallas

View shared research outputs
Top Co-Authors

Avatar

Ankur Das

Dayalbagh Educational Institute

View shared research outputs
Top Co-Authors

Avatar

Gursaran Srivastava

Dayalbagh Educational Institute

View shared research outputs
Top Co-Authors

Avatar

Ashok Kumar

Grand Valley State University

View shared research outputs
Researchain Logo
Decentralizing Knowledge