ICAPS 2020
Permanent URI for this collectionhttp://repository.kln.ac.lk/handle/123456789/21780
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Item Developing a model to identify the factors affecting customer satisfaction and their impact on third party logistics services in Sri Lanka(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Egodawela, S. M. D. T. K.; Peter, S.; Wijayanayake, A.Locating on a major east-west trade route near India, Sri Lanka has significant geographic advantages that are necessary to become a major logistics hub in South Asia. Despite its underdeveloped economy, the island country's total trade volume is around $ 88.9 billion (2018), making it a major hub for the region. A number of shipping lines use this site to, consolidate and deconsolidate cargo for transhipping to various destinations. Considering logistics performance, Sri Lanka was ranked 94th out of 167 countries according to the World Bank’s 2018 Logistics Performance Indicator (LPI). Therefore, Sri Lankan Logistics and Freight Forwarder Association has identified that the country needs to move up on the index, while providing a competitive service to the customers’ need. Both practitioners and scholars recognize the fact that embracing corporate sustainability as well as enhancing customer satisfaction can produce several relevant business benefits such as decrease of the intention to switch. Although past research captures the relationship between customer satisfaction and service quality through a combination of the SERVQUAL (service quality) model or the SERVPERF (service performance) model, however, the controllable factors may influence this relationship when considering the Third Party Logistics (3PL) industry in Sri Lanka. The model developed explores both service and performance, and other controllable factors affecting on customer satisfaction and their impact on the 3PL industry in Sri Lanka. It considered all key influencing factors and their relationship with each other using a systematic review process and complemented by reviews from industry experts. The model constructs include relationship performance as the independent variables while the impact of the 3PL industry on customer satisfaction has been measured using customer loyalty, customer switching behaviour and customer complaints which also been considered as dependent variables. Tech initiation has been recognized as a moderator variable for the operational performance and the Organizational image has been recognized as a controllable variable of customer satisfaction. The study results show that there is a statistically significant impact of the overall dimensions on the customer’s satisfaction and it implies that 8.09% of customer Loyalty depends on the above four independent variables and 18.85% of Switching Behaviour and 6.30% of Customer Complaints depends on all the independent variables. The proposed model which has verified will lead 3PL service providers, to distinguish significant factors, which have a considerable effect on the customer satisfaction. Further, the outcomes would assist the 3PL providers to minimize customer switching behaviour and switching costs, as they have a clear idea about the expectations of customers that should be fulfilled when delivering 3PL services.Item Framework to select the most suitable production line in an apparel firm in Sri Lanka: use of Analytical Hierarchical Process(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Thalagahage, N.T.H.; Niwunhella, D.H.H.; Wijayanayake, A.The apparel industry is considered as one of the most labour-intensive industries in the world despite the technological advancements and the amount of automation. Line planning in the garment industry is the process of scheduling and allocating production orders to production lines according to the product setting and due dates of manufacturing completion. Most of the apparel manufacturers in Sri Lanka have switched to lean model production, in which large sewing departments are split into smaller, self-balancing sewing lines. The decisions that address the production line selection process for a particular production order still heavily rely on production planners, based on their experience. These decisions tend to be neither consistent nor scientific because of the lack of interdepartmental connectivity. Little emphasis has been placed on the impact of the planning considerations and ways to apportion certain production orders to the appropriate production system with specific characteristics. This problem is addressed in the research through the development of a multi criteria decision making framework to enable the incorporation of all the parameters to select the best production line for a particular sales order using Analytical Hierarchical Process (AHP). AHP method is adopted for decision making which models multiple, possibly conflicting factors dependent on each other and it makes appropriate trade-offs to recommend well-balanced solutions to different stakeholders. The production line selection criteria identified through expert opinions and literature review were applied in the AHP conceptual model. 23 factors were identified and they were categorized under 5 areas which are characteristics of the product, characteristics of the production order, characteristics of the production line, technical support and quality parameters. In order to build the AHP model, 4 manufacturing firms and 4 senior and middle level managerial industrial experts from each firm were selected and interviewed through AHP questionnaires. After the pairwise comparisons, each criterion was weighted and prioritized. Most of the interviews resulted in high priority for delivery date, technical infrastructure, skills inventory of the line, the efficiency of the line, and cadre requirement while the ability to adopt changeovers, prioritization of machine service, and infrastructure support by the technicians were given low priorities. This interprets that, for any kind of a production order the mostly prioritized criteria are important to be considered. Therefore, focusing on them in line selection would lead to improved planning efficiency. After the criteria comparison, each alternative production line was given a score against the planning criteria and the production lines were ranked in order to select the best production line. Through data analysis, it was found out that the results obtained from different industrial experts representing different apparel manufacturing firms vary from each other depending on individual perspective and policies inherent to the manufacturing firm. However, the framework can relate to any apparel manufacturing firm by allowing Decision Makers to select the valid criteria depending on the Production Order and its related parameters. Also, the framework can be used for other manufacturing industries with few modifications and assumptions. In order to avoid the subjectivity in AHP method, a Linear Programming model can be developed as a future improvement and optimize the production lines selected through AHP ranking.Item Cost minimization model through consolidation: application to a third party logistics distribution center(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Weerakkody, H.D.W.; Niwunhella, D.H.H.; Wijayanayake, A.Third Party Logistics (3PL) providing industry has become an essential service for the manufacturers due to the numerous benefits they could obtain by outsourcing their logistics activities to a 3PL provider. When considering the 3PL industry in Sri Lanka, growth can be seen in the past few decades. Since the distribution of goods of multiple clients in a 3PL Distribution Center (DC), is handled by the 3PL providers, they are much interested in minimizing the distribution cost which will not only ultimately benefit to the 3PL provider but also the client as well. However, managing the distribution of multiple clients at the same time with an optimized cost is challenging for 3PL service providers. The consolidation of goods of multiple clients in the distribution process is one of the main cost-effective strategies that the 3PLs could use. But due to several reasons such as compatibility constraint of goods transported, client concerns, complicated scheduling, consolidation is not practiced by many of the 3PLs in Sri Lanka. Therefore, this study was conducted on identifying the main factors to be considered when consolidating goods of multiple clients, and to develop a mathematical model to minimize the distribution cost in a 3PL DC by shipment consolidation. This paper proposes a mathematical model considering the Vehicle Routing Problem (VRP) as an extension found in the literature, where the compatibility of the products distributed has been added as a new constraint. The mathematical model has been tested and validated using the actual data obtained from few of the 3PL firms in Sri Lanka and has been simulated using the Supply Chain Guru Software. Different scenarios are created in the software to check the feasibility and accuracy of the model. The results obtained showcase an average cost reduction of nearly 25% when consolidating shipments of multiple clients in a 3PL DC. Therefore, it is evident from the study that, the 3PL firms could obtain a significant cost reduction by consolidating shipments of multiple clients. It was also identified that factors like compatibility of the distributed goods, cargo tonnage, clients’ privacy concerns and scheduling of shipments should be considered when consolidating goods of multiple clients to distribute in a 3PL DC. The findings of this research will help the 3PL providers to consider consolidating shipments of several clients and the mathematical model proposed in the research will help them to minimize the distribution cost. Furthermore, the trucks can be properly utilized, the number of trucks and fuel wastage can be reduced and the impact on the environment will be lesser. Future researches could be done on adding more complexity to the model by considering different constraints such as time windows for the orders.Item Developing a model for effective supplier selection using Analytic Network Process (ANP)(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Udakanjalee, H.I.; Niwunhella, D.H.H.; Wijayanayake, A.If any organization needs to survive in this intensively competitive market, they should possess a competitive advantage over other companies. An effective supplier selection process is a major determinant of the degree of competitive advantage within an organization. The common drawbacks in the existing supplier selection processes which hinder the selection of effective supplier/suppliers are the absence of a systematic mechanism and subjectivity of decisions. It is also a disadvantage from suppliers’ perspective, as a supplier cannot systematically align their processes because requirements and expectations differ from organization to organization. Therefore, the objective of this research is to propose a mechanism and a general model to prioritize criteria, sub criteria, and alternative suppliers along with appropriate set of criteria and sub criteria and to validate it across few industries. With the scope of this paper, supplier selection was considered as a multi criteria decision making problem (MCDM) because supplier selection is the evaluation of trade-offs between inconsistent, contradictory and competing criteria with each other. Analytic Network Process (ANP) which is a technique to solve MCDM problems in which the criteria affect each other and have nonlinear correlation, is used here to prioritize criteria and alternatives. In this study, a systematic review of literature was conducted to identify the different research approaches, limitations, and gaps and to determine most appropriate criteria, sub-criteria, tools and techniques used for supplier selection. Then developed the tentative criteria list and tentative ANP model using data gathered through literature review. Then this model and criteria list was finalized through a survey in a chemical manufacturing company, by acquiring industry experts’ opinion. After finalizing the model, it is validated by feeding data obtained through past supplier selection records into it. Here results were compared and constructed with the actual results in each case. The results of the survey show that most important criteria that should consider when selecting suppliers for the selected product in this chemical manufacturing company are the production capability, delivery capability, financial capability and service capability of the supplier. In the current supplier selection process in this company, they consider only factors like the quality and price of product and punctuality delivery goods by suppliers. But these limited set of criteria have led to choosing ineffective suppliers. The result of this study shows the scope and the importance of criteria and sub criteria that should be used for supplier selection in this company. Here when comparing these results with past literature, it can be concluded that industry wise prioritizations are not exactly similar but can relate to general model with few modifications and assumptions. Also, when comparing the finalized model and mechanism with past literature it can be concluded that this model is more appropriate for large scale manufacturing companies who are mainly focusing on exports, procuring products than services, procuring products use as the raw materials in manufacturing processes.Item Comparison of rainwater quality of three areas located in the vicinity of an oil refinery and thermal power plant in Sri Lanka(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Hirushan, H.H.; Deeyamulla, M.P.The chemical composition of rainwater, a form of wet deposition, differs over time due to a broad range of physical, chemical, and biological factors. The purpose of this analysis was to establish and compare the key ionic composition and water quality parameters of bulk deposition samples considering rainfall patterns, rainfall rates and pollutant sources. Three sampling sites were selected for the study in the Gampaha District in Sri Lanka which were separated by 7 km from each other. The first site was in the Makola South (MS) which represented an area in the vicinity of an oil refinery and thermal power plants; the second and third sites were in the University of Kelaniya (UOK) and Orugodawatta (OW) respectively, representing urban environments. Bulk depositions were collected after the container was almost filled avoiding any overflow. The chemical analyses of anions (F- , Cl- , NO3 - , SO4 2- ) in bulk depositions were carried out using the Dionex ICS-900 ion chromatography system and metals (V, Cr, Mn, Fe, Ni, Cu, Zn, As, Cd, Pb) were analyzed using the ICP-MS 7800-Agilent system. The average pH in MS, UOK and OW sites was 6.70, 7.15 and 7.31 respectively, and it was almost neutral due to atmospheric neutralization. The average conductivity values of MS, UOK and OW sites were 40.96 µScm-1 , 35.63 µScm-1 and 38.93 µScm-1 , respectively. The average values of other water quality parameters (salinity, TDS) were higher in the MS site than the other sites. The dominant metals were Na, Cr, Fe, Cu, As, and SO4 2- was the dominant anion in the MS site than the other two sites showing the pollution may be due to the influence of oil refinery and the thermal power plants situated near the MS site. The results indicated that the metal concentrations, anion concentrations and the water quality parameters from the rainwater collected among the MS, UOK and OW sites, the MS site has higher concentrations and higher pollution due to its location being in the vicinity of the oil refinery and thermal power plant. According to the results obtained it can be stated that rainwater analysis can be used as an indirect method to determine ambient air quality.Item Developing a methodology for evaluating the sustainability performance of logistics service providers using AHP(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Prabodhika, A.P.K.J.; Niwunhella, D.H.H.; Wijayanayake, A.Sustainability and sustainable development have become a buzzing topic in today's business world. Business organizations are now more towards making themselves more economically, socially, and environmentally sustainable. With the introduction of concepts like “Sustainable Supply Chain Management” organizations have determined not only to make themselves sustainable but also to make the whole supply chain sustainable as well. Many manufacturers and retailers often outsource their logistics functions to Logistics Service Providers (LSPs) to focus more on their core business process. Due to the competitiveness and the popularity of the sustainability concept, those organizations evaluate their prospective LSPs not only based on economic aspects like cost, service quality but also on social and environmental aspects as well. This paper proposes a methodology for evaluating the sustainability performance of LSPs using the Analytical Hierarchy Process (AHP). A Composite Sustainability Performance Index (CSPI) was developed using AHP since multiple dimensions and indicators need to be incorporated when measuring the sustainability performance and composites indices assist in aggregating all dimensions and indicators into a single measurement which will be easy to interpret, compare and benchmark. CSPI can be used by organizations when selecting the LSPs as their business partners based on the performance of three traditional dimensions of sustainability; Economic, Social, and Environmental, and a newly included technological aspect. The proposed methodology is flexible as it depends on the sustainability requirements of a particular organization when selecting LSPs as the relative importance of the dimensions and its indicators are up to the organization to decide. Analytic Hierarchy Process (AHP) has been used to create a model and give relative importance for each dimension/indicator and then the sub-dimensions or sub-indicators under each dimension are compared. Weighted and evaluated indicators are then aggregated using linear additive aggregation to construct the CSPI based on which the LSPs can be evaluated. This proposed model enables the selection of the best LSP according to the organization's preference or requirements. The proposed methodology was then used to compare and select the 3 prospective LSPs of an apparel manufacturing organization using the data obtained through interviews and questionnaires. According to the results, the highest importance of the organization was given to the economic dimension (0.5498), then to environmental (0.2748), then social (0.1202), and least to the technology dimension (0.0554) by the decision-makers. CSPI values are computed as 3.6863, 3.1644, 3.3044 for LSP 1, LSP 2, LSP 3, respectively. Among them, the highest values were obtained by LSP 1 which is 3.6863 and it is the best selection among the three alternatives. The reason LSP 1 got the highest CSPI is, it has performed best in the highly weighted sustainability performance indicators by the organization when compared to the other two LPSs.Item Classifying risk and vulnerability in the supply chain during an epidemic outbreak(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Perera, M.A.S.M.; Wijayanayake, A.; Peter, S.Companies always try to maximize shareholders' value by reducing the cost and maximizing profits in the long terms. However, one of the primary difficulties they face in doing so, is because of disruptions in the supply chain (SC). The supply chain can be disrupted due to natural disasters, manmade catastrophes, strikes, legal disputes, and special cases like epidemic outbreaks. The study explores what causes the supply chain to be disrupted in a company during an epidemic outbreak. It focuses on the Sri Lankan apparel industry as it contributes 6% to Sri Lanka’s GDP and 44% percent to Sri Lanka’s National Export Revenue, which is a significant proportion of the country’s economy. The primary objective of this study is to identify the supply chain risks in order to be prepared, mitigate the effects and ensure business continuity. The study proposes a model to identify the SC risks and vulnerabilities during an epidemic outbreak, and which risks should be prioritized. The model was primarily developed through a systematic review of literature and information collected from experts in the apparel sector was used to validate the findings. Leading apparel manufacturing companies in Sri Lanka were selected through convenience sampling and managers with more than five years’ experience were selected through random sampling. Using the output, the identified risks are then analysed and mapped in a vulnerability matrix considering cost and time factors. The model was tested and validated using 80%-20% rule. 80% of the collected data was used to develop the model and 20% of the collected data was used for testing and validation. Moreover, experts’ opinions were also used to validate the vulnerability matrix. Loss of local key supplier, loss of international key supplier, local port closure, international port closure, transportation link disruption (other than ports), raw materials delays and shortages, human resource shortages, product demand variations, order cancellations and lead time variations are SC risks which are considered for this study. The loss of international key suppliers and order cancellations were classified as high risks, whereas, human resource shortages were classified as the least risk. Though, a generalized vulnerability model is developed in this study considering cost and time factors, it can be customized using different factors and risks depending on the experience and needs of the company. Participants for the survey assumed that customers are international, and suppliers are both local and international. The study can be further developed to identify the SC strategies which should be taken to mitigate the SC disruptions during an epidemic outbreak or during a major global crisis.Item Identifying the key success factors in third party logistic services: Sri Lankan context(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Perera, D.G.T.M.; Wijayanayake, A.; Wickramarachchi, A.P.R.To be more cost-effective as well as to maintain a sustainable competitive advantage, many enterprises tend to improve their business practices by having a strong relationship with thirdparty logistics (3PL) service providers. 3PL service providers mainly focus on warehousing, inventory management and control, planning, cross-docking and transportation. By outsourcing such processes, enterprises gain benefits such as reducing costs, improving product quality, and improving the flexibility of operations. Sri Lankan 3PL service providers also provide many services for their clients but compare to other countries Sri Lanka is facing more challenges including poor infrastructure, complex tax regulations, insufficient use of technology and limited service offerings. According to the World Bank’s Logistics Performance Indicator ranking (LPI) for 2018, Sri Lanka is ranked 94th out of 160. Compare to the previous year Sri Lanka’s rank has dropped down. This indicates a need for Sri Lanka to improve the quality of its logistics services. Better performance of the 3PL service providers is one factor which can contribute to improving the quality of logistics services. Therefore, it is important to investigate key success factors of 3PL industry in Sri Lanka which can support to increase the performance of 3PL service providers. The main objectives of this paper are to determine key success factors associated with the Sri Lankan 3PL industry and prioritize those key success factors. This study used the systematic literature review and expert’s opinion to identify the key success factors of 3PL industry in Sri Lanka. In total, 20 key success factors were obtained, and those key success factors were grouped into four categories as organization strategy, management and process, human resources and customer orientation. The study used the Q-sort technique to group key success factors into four categories and Analytic Hierarchy Process (AHP) to identify the priorities of the key success factors. Survey analysis is conducted with four Sri Lankan 3PL service providers to collect the data. Data were collected through questionnaires from executives, middle and seniorlevel managers of 3PL firms who got more than least five years of experience in 3PL industry. Totally, 36 experts in 3PL industry have participated in the data collection process. The geometric mean was used to consolidate different experts’ opinions to a single value in pairwise assessment matrix. The result shows that business expansion, technology and automation, internationalization of operations, management and leadership style are the most important key success factors in the Sri Lankan 3PL industry. These factors explain that most of the Sri Lankan 3PL service providers are currently in the growth stage of the 3PL industry and these key success factors will lead them to reach the maturity level. Therefore, managers need to focus more on these factors to increase the performance of 3PL companies. This is the first research that addresses the key success factors of 3PL industry in Sri Lanka. The outcomes of this study can help managers/practitioners to formulate flexible decision strategies for better performance in their 3PL firms and experience a competitive advantage against the competitors.Item Finding an efficient solution system for leaching extractable proteins from natural rubber gloves(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Dikella, D.G.W.N.; Jayasuriya, C.K.; Premachandra, B.A.J.K.Natural rubber latex (NRL) is used to manufacture a large number of useful products such as gloves. Allergy to NRL gloves is caused by latex proteins extractable into sweat. Extractable proteins (EP) come in contact with the skin causing allergic reactions. The protein allergy caused by latex products has become an acute problem to human health. Certain proteins or peptides eluting from NRL products can cause immediate hypersensitivity reactions (Type I allergy) in people sensitized to those proteins. The amount of total EPs in NRL gloves was assumed to reflect their corresponding amount of allergenic proteins. The major objective of this research was to develop an economical method to reduce EPs in finished NRL gloves. The current study was focused on developing a leaching solution system to remove the extractable NRL proteins from the gloves using CaCl2 solution and sodium dodecyl sulphate (SDS) solution. Rubber films were leached with varying aqueous CaCl2 (5%, 10%, 15%, w/v%) concentrations followed by leaching with SDS (5%, w/v%). After leaching, the water extractable proteins were analyzed by the analytical methodology based on the modified Lowry method according to ASTM D5712. Distilled water leached samples were used as the reference. When CaCl2 concentration in leaching was increased, the removal efficiency of EPs was increased. When the samples were leached with CaCl2 followed by SDS, they illustrated a further reduction of EPs. Thus, the amount of remaining EPs in the product decreased considerably. A maximum removal efficiency could be seen when the rubber films were leached with CaCl2 (15%, w/v%) followed by SDS (5 %, w/v%). The effect of leaching solvents on the final product was analyzed by measuring the mechanical properties such as tensile strength, tear strength and aging resistance. Distilled water leached samples were used as the reference. The mechanical properties did not change to a greater extent when rubber films were leached with CaCl2 followed by SDS when compared to that of water leached samples. Therefore, leaching rubber gloves with CaCl2 (15%, w/v%) followed by SDS (5%, w/v%) may be an efficient method for reducing EP content of the final product and thus reducing the allergenic conditions of sensitized people for NRL gloves.Item Estimating separability of magnetisation signals by fast implementation of Bloch equation simulations across multiple tissues and distance correlation function(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Iddagoda, M.; Jayaweera, H.H.E.; Wansapura, J.Magnetic Resonance Fingerprinting (MRF) is an emerging field in Magnetic Resonance Imaging (MRI) where tissues to be identified are subjected to a series of magnetic pulses. The resulting magnetisation signal is governed by both the tissue properties as well as the chosen pulse acquisition parameters. By employing a suitable classifier, the tissue properties are recovered from the magnetisation signal in MRF. Depending on the chosen pulse acquisition parameters, the resulting magnetisation signals must be unique for different tissue properties for MRF to be effective. But the acquisition parameters of magnetic pulses in MRF are traditionally chosen in random. Hence, it is possible that the magnetic signals for tissues of concern may not be sufficiently distinguishable for efficient classification. Therefore, to explore the possibility of optimising the level of separability of magnetisation signals of different tissue types, optimal values of acquisition parameters of the pulse sequence must be carefully engineered. This task requires means of estimating the level of separability of magnetisation signals for different tissues. In this study, a fast simulation mechanism is implemented that estimates the level of separability of magnetisation signals generated in MRF for a chosen set of tissue properties and pulse acquisition parameters. An in-house built Bloch equations simulator was used to model nuclear magnetisation of atoms for both Balanced Steady State Free Precession (BSSFP) and Echo Planar Imaging (EPI) pulse sequences with variable pulse acquisition parameters. For the two pulse sequences chosen, calculating the magnetisation signal for a single tissue is sequential by nature. However, the calculations are parallel when repeated across multiple tissues. Therefore, the simulator was implemented on a Graphical Processing Unit (GPU) to exploit the parallel nature of the problem and to shorten execution time. To determine the level classification of magnetisation signals, distance correlation Function, which measures both linear and non-linear association between two signals was chosen. Since for N number of tissues, there are NC2 number of correlation computations, the computational demand will be prohibitively expensive with higher numbers of tissues. Therefore, the distance correlation which, given the parallel nature of calculations, was reformulated as a series of array operations to be able to execute in the GPU. It was observed that as compared to a CPU only implementation, GPU execution of Bloch equation calculations sped up significantly. Through reformulation as array operations, calculation of distance correlation, which computationally is more expensive than Bloch equation simulations, sped up roughly by a factor of 10,000 times. With the fast execution time through GPU, the implementation provides practical means of evaluating a vast number of tissues to indicate the level of separability for a chosen set of pulse acquisition parameters within a few seconds. Therefore, the system developed facilitates a designer to carefully engineer the optimal pulse sequence parameters to ensure that the magnetisation signals generated are efficiently classifiable prior to carrying out physical scans for MRF using the MRI machine.