Towards a Process to Guide Big Data Based Decision Support Systems for Business Processes

Vera-Baquero, Alejandro; Colomo‐Palacios, Ricardo; Molloy, Owen

doi:10.1016/j.protcy.2014.10.063

Cited by 38 publications

(12 citation statements)

References 7 publications

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“…Taking into account the high costs of robotic production lines, it is necessary to develop flexible production systems that will allow for quick adaptation to customers’ needs. This solution is possible thanks to the use of techniques and tools for the analysis of the current technological process with the possibility of predicting future functions of the system [ 6 , 7 , 8 , 9 , 10 , 11 , 12 ]. It is a good habit, when estimating the requirements of the process and creating behavioral models of both the process and individual machines, to consider possible problems and include them in this model.…”

Section: Introductionmentioning

confidence: 99%

Selection and Optimization of the Parameters of the Robotized Packaging Process of One Type of Product

Borys

Kaczmarek

Laskowski

2020

Sensors

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The article presents the results of computer simulations related to the selection and optimization of the parameters of robotic packing process of one type of product. Taking the required performance of the robotic production line as a basis, we proposed its configuration using the RobotStudio environment for offline robot programming and virtual controller technology. Next, a methodology for the validation of the adopted assumptions was developed, based on a wide range of input data and a precise representation of the applicable conditions in the packaging process of one type of product. This methodology included test scenarios repeated an appropriate number of times in order to obtain the result data with the desired reliability and repeatability. The main element of the research was a computer simulation of the station based on the Picking PowerPac package. It was assumed that the products on the technological line are generated pseudo-randomly, thus reflecting the real working conditions. The result of the conducted works is the optimal operating speed of industrial robots and conveyors. The developed methodology allows for multifaceted analyses of the key parameters of the technological process (e.g., the number of active robots and their load, speed of conveyors, and station efficiency). We paid special attention to the occurrence of anomalies, i.e., emergency situations in the form of “halting” the operation of chosen robots and their impact on the obtained quality of the industrial process. As a result of the simulations, numerical values were obtained, maximum efficiency, with regard to maximum overflow of items of 5%, for LB algorithm was equal to 1188 completed containers per hour, with conveyors speeds of 270 mm/s and 165 mm/s. This efficiency was possible at robot speeds R1 = 6450 mm/s, R2 = 7500 mm/s, R3 = 6500 mm/s, R4 = 6375 mm/s, R5 = 5500 mm/s, R6 = 7200 mm/s. The ATC algorithm reached efficiency of 1332 containers per hour with less than 5% overflown items, with conveyor speeds of 310 mm/s and 185 mm/s. This efficiency was possible at robot speeds R1 = 7500 mm/s, R2 = 7500 mm/s, R3 = 7200 mm/s, R4 = 7000 mm/s, R5 = 6450 mm/s, R6 = 6300 mm/s. Tests carried out for emergency situations showed that the LB algorithm does not allow for automatic continuation of the process, while the ATC algorithm assured production efficiency of 94% to 98% of the maximum station efficiency.

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Section: Introductionmentioning

confidence: 99%

Selection and Optimization of the Parameters of the Robotized Packaging Process of One Type of Product

Borys

Kaczmarek

Laskowski

2020

Sensors

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“…The notions of big data (BD), risk management (RM) and business process (BP) have all received attention from researchers and practitioners over the past few decades; indeed, research interest in these areas has been steadily increasing in recent years. To the authors' knowledge, however, although the relevant literature examines individually the concepts of BD, RM and BP or does so jointly -BD and BP (Vera-Baquero et al, 2014); BD and RM (Frankel, 2012); RM and BP (Suriadi et al, 2014) -no studies consider these three elements together within the real estate sector; further, nothing is known about what encompasses these three concepts in CRE. Based on these considerations, the aim of this paper is to improve understanding of the integration between BD and RM in BPs, with special reference to CRE.…”

Section: -Introductionmentioning

confidence: 99%

Big data and risk management in business processes: implications for corporate real estate

Battisti

Shams²,

Sakka

et al. 2019

BPMJ

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Purpose The purpose of this paper is to improve understanding of the integration between big data (BD) and risk management (RM) in business processes (BPs), with special reference to corporate real estate (CRE). Design/methodology/approach This conceptual study follows, methodologically, the structuring inter-textual coherence process – specifically, the synthesised coherence tactical approach. It draws heavily on theoretical evidence published, mainly, in the corporate finance and the business management literature. Findings A new conceptual framework is presented for CRE to proactively develop insights into the potential benefits of using BD as a business strategy/instrument. The approach was found to strengthen decision-making processes and encourage better RM – with significant consequences, in particular, for business process management (BPM). Specifically, by recognising the potential uses of BD, it is also possible to redefine the processes with advantages in terms of RM. Originality/value This study contributes to the literature in the fields of real estate, RM, BPM and digital transformation. To the best knowledge of authors, although the literature has examined the concepts of BD, RM and BP, no prior studies have comprehensively examined these three elements and their conjoint contribution to CRE. In particular, the study highlights how the automation of data-intensive activities and the analysis of such data (in both structured and unstructured forms), as a means of supporting decision making, can lead to better efficiency in RM and optimisation of processes.

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“…Data driven decisions are critically important in many application domains. Data has become a highly valued resource and requires appropriate security assurances [2]. A major concern in data security is the assessment of data integrity in untrusted servers with respect to large data in cloud platforms [3].…”

Section: Introductionmentioning

confidence: 99%

Enhancement Data Integrity Checking Using Combination MD5 and SHA1 Algorithm in Hadoop Architecture

Idris¹,

Ismail²,

Azmi³

et al. 2017

JCSCM

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The use of Big Data in decision-making is critical, in line with the growing size of data storage, either online or offline. However, there are only a few software applications that are capable to process large-capacity data such as Hadoop. Hadoop is open-source software for Big Data processing including several components joined together where one of its main components is Hadoop User Experience (Hue).

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Towards a Process to Guide Big Data Based Decision Support Systems for Business Processes

Cited by 38 publications

References 7 publications

Selection and Optimization of the Parameters of the Robotized Packaging Process of One Type of Product

Selection and Optimization of the Parameters of the Robotized Packaging Process of One Type of Product

Big data and risk management in business processes: implications for corporate real estate

Enhancement Data Integrity Checking Using Combination MD5 and SHA1 Algorithm in Hadoop Architecture

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