A combination of three engineering tools for identifying and evaluating the possible failures of a process

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RELAZIONE PER IL CONSEGUIMENTO DELLA LAUREA MAGISTRALE IN INGEGNERIA GESTIONALE

A Combination of Three Engineering Tools for

Identifying and Evaluating the Possible Failures of a

Process

RELATORI IL CANDIDATO

Prof. Ing. Gionata Carmignani Roberta Zanni

Dipartimento di Ingegneria dell’Energia dei Sistemi,

del Territorio e delle Costruzioni roberta_zanni@msn.com

Sessione di Laurea del 03/05/2017 Anno Accademico 2015/2016 Consultazione NON consentita

2 Abstract: This paper presents a combination of three engineering tools, i.e. Dysfunctional Mode

and Effects Critical Analysis (DMECA), Fault Tree Analysis (FTA) and House of Reliability (HoR), for identifying and evaluating the possible failures of a process. These tools are well known in the academic and industrial world. The methodology presented joined the strengths of them to analyze at the same time both the effects and causes of failures. Working for preventing or reducing them lead sometimes to avoid the failures of some activities of the process. This combination enables users to:

 analyze each activity of a process

 evaluate each potential failure and his causes

 evaluate a Risk Priority Number (RPN) for each cause considering the degree of importance of each effect

 study the relationship between causes and between causes and effects  support the definition and evaluation of the possible improvement actions

First there is a briefly description of the strengths of these tools. Then, in order to illustrate the methodology there is an industrial application, i.e. for the delivery process of a famous company in the media-entertainment sector.

1. Introduction

According to ISO 31000:2009, Risk management – Principles and guidelines, risks affecting organizations can have consequences in terms of economic performance and professional reputation, as well as environmental, safety and societal outcomes. Therefore, managing risk effectively helps organizations to perform well in an environment full of uncertainty. For these reasons the risk management function has grown rapidly in organizations over the last two decades with shareholders, regulators, professional bodies and rating agencies pushing for better corporate governance and internal control (Bhimani, 2009; Power, 2007; Soin & Collier, 2013). So, risk management can be understood as a structured process to minimize or mitigate the effects of risks (Wang and Hsu, 2009), or a proactive process of decision making that aims to minimize the consequences of negative future events, by identifying potential risks, analyzing them and planning the responses necessary for their monitoring and control (Mabrouki et al.,

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2014, Ualison Rébula de Oliveira et al., 2017). Many organizations, both public and private,

experienced several tools and methodologies connected to risk management in different sectors

to create value and improve performances. S. Ali Torabi, Ramin Giahi and Navid Sahebjamnia

(2016), for example, explain how an effective risk management system should be implemented to gain the organization business continuity with a case of a real service organization named as the organization X (due to confidentiality), which is in charge of disaster management services in city of Tehran. The major part of the applications concern manufacturing companies where the tools of risk management are applied to physical products and recently to processes. Fera and Macchiaroli (2010) present a mixed qualitative-quantitative Risk Assessment method for assessing the safety risks in the small and medium enterprises (SMEs). The authors introduce three steps for safety RA including the: (1) building a team to identify risks and comparing them with each other, (2) assessing them through a quantitative model to calculate the frequency and consequences of each identified risk and, (3) finally, providing improvement actions. Lai and Lau (2012) present a risk management model in order to manage the risks of a textile manufacturing company. In this framework, the potential risks are first identified. Then likelihood, consequence, and the amount of risks are obtained. Afterwards, the risk assessment matrix is divided into the four regions according to the impact and likelihood of risks. Finally, four actions are suggested as the risk response plans according to these four regions. These plans include: accept the risk (for those with low likelihood, low impact), avoid the risk (for those with high likelihood, low impact), transfer (for those with low likelihood, high impact), and mitigate (for those with high likelihood, high impact). Samantra et al. (2014) present a quantitative methodology in which those risks related to information technology outsourcing are assessed. The authors introduce four major steps for the methodology: (1) identifying the risks within the context of information technology outsourcing, (2) collecting aggregated linguistic data about the likelihood and the impact of risks from the experts’ opinions, (3) calculating the amount of each risk by multiplying the respective likelihood and impact (4) developing suitable action plans for treating the risks. Marhavilas and Koulouriotis (2012) present a framework for safety risk assessment in the work sites, studying the Greek Public Electric Power Provider. In this framework, potential hazards are identified and their frequencies and consequences are analyzed using gathered relevant statistical data. After evaluating the hazards’ quantities, suitable decisions about them are made (i.e. whether accept or mitigate each hazard). Wulan and Petrovic (2012) present a framework for risk assessment

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within the context of enterprise collaboration. In this framework, different risks in the life cycle

of enterprise collaboration including the pre-creation, creation, operation and termination are

first identified. Then, the probability and impact of each risk are determined by fuzzy linguistic terms. The proposed framework is also tested in an automotive company. Risk management can

also be used to prevent and reduce injuries, like Keshia M. Pollack et all. (2017) explain in their

article. They used risk management, as a proactive process to identify and mitigate potential injury risks and implement control strategies, to reduce the risk of occupational injury in the U.S. fire department. The first objective was to study the implementation of the risk management process for future replication. The second objective was to document changes in fire personnel's knowledge, attitudes, and behaviors related to the selected control strategies that were implemented as part of the risk management process. In the context of service organizations the tools of risk management are used almost for managing information security risk. Ou Yang et al. (2013) present a method to assess information security risks. In this paper, after identifying the risks, three multi criteria decision making approaches, i.e., VIKOR, DEMATEL, and ANP, are combined to assess the identified risks. The proposed method is also applied in an information technology company. Feng et al. (2014) propose a model to analyze security risks of information systems. A Bayesian network is also utilized to determine risks and their associated causal pathways. Finally, the proposed model is applied in a service company’s information system. Silva et all. (2014) explained in their framework how organizations have become more susceptible to attacks on Information Technology Systems because of the evolution and widespread use of the Internet. To minimize the potential failures they present an approach to information security risk management, encompassing Failure Mode and Effects Analysis (FMEA) and fuzzy theory. This approach analyses five dimensions of information security: access to information and systems, communication security, infrastructure, security management and secure information systems development. To illustrate the proposed model, it was applied to a University Research Group project. The results show that the most important aspects of information security risk are communication security, followed by infrastructure. Nowadays one of the most relevant scope of the tools of risk management is to mitigate external risks to gain business continuity. For this reason, there are many studies focused on the supply chain, the natural companies’ interface with the external environment. Ualison Rébula de Oliveira et all. (2017), for example, applied the ISO 31000 standard as a standardized method to perform Supply Chain Risk Management

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(SCRM), as long as tools and techniques are selected according to the company needs and business characteristics. They developed a pathway to identify and prioritize which ISO 31000:2009 risk assessment tools and techniques are supposed to integrate a procedure for SCRM, based on the Analytic Hierarchy Process (AHP), exemplified in an automotive supply chain. Muchfirodin M. et all (2015) based their framework on ISO 31000:2009 too, for identifying and mitigating risks in tobacco supply chain in Temanggung Regency, Central Java Province, Indonesia. The mitigation plan was composed by using tool of analytical network process (ANP). The results showed that the risk that were classified as avoidance risk at farmer level are weather, capital access, the price and quantity. At the middlemen level are impurity of quality, capital access, the price and quantity. And at the level are supplier quality variances, capital access, the price and quantity. Based on the ANP method, the fit strategy to mitigate risk bothered by the development of seeding technology. Aqlan F. (2016), instead, proposed a software application framework for rapid risk assessment (RRA) in integrated supply chains. The proposed framework combines qualitative and quantitative methods to assess and prioritize the risks. Qualitative methods are based on surveys used to collect the risk probability and impact data for the main agents in the supply chain (i.e., supplier, customer, manufacturer, etc.). Quantitative methods are based on probability theory and fuzzy logic. Risks are calculated for each agent in the supply chain and are then aggregated per product type. The proposed RRA tool was tested in a manufacturing environment to assess the validity. Anggrahini D. et all. (2015) analyzed quality risks of frozen shrimp product along its supply chain, involving supplier, the company producing it, logistic provider and customer. Firstly, all the activities are mapped by using Supply Chain Operations Reference (SCOR) model, then are divided into five categories namely plan, source, make, deliver and return. Secondly, potential quality risks are analyzed in a House of Risk 1 (HOR-1). Furthermore, some mitigation actions are deployed, then being analyzed by using HOR-2. There are also some studies which have applied quantitative engineering methods to manage supply chain risk management, because of quantitative analysis of supply chain risk is expanding rapidly (Fahimnia M. et all. ;2015). An example is the framework of Bertolini et all. (2006), in which is presented an application of the ‘Failure Mode Effect and Criticality Analysis’ (FMECA) for the production process in the farming and food industries. The scope was to detect the possible critical points of its traceability system (including the operations about supply chain), and to

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context of supply chain risk management. They used Shannon entropy for the weighing of selection criteria and fuzzy TOPSIS is applied for ranking suppliers. Markmann et all. (2013) used Delphi technique to identify and assess risks associated with global supply chains. They illustrate how Delphi research makes a fivefold contribution to risk analysis by: (1) identifying and quantifying risks; (2) analyzing stakeholder perceptions and worldviews; (3) stimulating a global communication process; (4) identifying weak signals, outlier opinions, and wildcards; (5) and facilitating risk scenario development. Schoenherr et all (2008) used analytic hierarchy process (AHP) to assess supply chain risks in a US manufacturing company. Through iterative and structured discussions, 17 risk factors were identified, which were subsequently grouped into main and sub objectives. AHP was then used to evaluate the importance of each risk factor, and

to determine the best alternative.Reuven R. Levary (2008), instead, used AHP to rank potential

suppliers. A case study is presented in which a manufacturer evaluates and ranks its current

foreign supplier against two other potential foreign suppliers based on several criteria of supply reliability. Despite the several studies about supply chain risk management, companies who apply it are few and are almost in manufacturing sector. Furthermore, according to Ghadge et al. (2012) and Colicchia and Strozzi (2012), there are many sources of risks, which can originate within the company (operational risks) or in the external business environment (rupture risks), since the uncertainty of the business climate and the complexity of supply chains increase the likelihood of breakdowns. There is also a lack of consensus among researchers as to the steps that should be included, both regarding their number and the actions involved. For example, Wu et al., (2006) advocate that SCRM should be carried out in a process with at least three steps, which differ in their procedures according to the three research groups. Other authors, like Hallikasa et al., 2004, argue for different procedures, with more than three steps. At the upper extreme, Ritchie and Brindley (2007) defend the conduction of seven steps for supply chain risk

management. Nowadays outsourcing functions such as logistics has become an industry trend

towards cost-effectiveness and high service level performance. Many firms have acknowledged the benefits of relying on external experts in a need to empower their abilities (A. El Mokrini

2016). Therefore, especially for these companies, which commit some activities of the supply

chain to external suppliers (for example delivery activities), is fundamental to have some tools to identify, evaluate and manage the possible risks. Moreover, managers need easy, flexible and more visual tools (i.e. graphics and schemes), that are fast to consult and understand. However,

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there isn’t a simple and quick method with definite steps to follow. Another aspect to consider is that almost none of the studies in literature investigate the causes of risks, to prevent the occurrence of risks. Failures causes, instead, are fundamental for studying a process, because sometimes changing some process activities is the best way to prevent or significantly reduce risks. The well-known tools, like FMECA, FTA or Fuzzy Theory, are very flexible and can be adapted in most of all situations, but they are incomplete used alone. FMECA for example it used to evaluate failures but not their causes. Therefore to fill this gap, this framework propose a combination of three engineering tools (the Dysfunctional mode and effect criticality analysis-DMECA, the Fault tree analysis-FTA and the House of Reliability-HoR) for identifying, evaluating and managing the causes of possible failures for the activities of a process. Each tool has strengths and weaknesses and combining their strengths permits to have a complete analysis of both failures and their causes at the same time. This method can be applied to all processes in any business sector and permit to obtain a rank of the causes of failures, and to concentrate effort and money for managing the most impactful. In the following section (2) there is a short description of the most relevant engineering tools, which can be applied in the field of risk management. In section (3) is described the methodology, step by step, for applying the three tools to a process. Specifically this method is used to identify and evaluate the causes of possible failures of the delivery process in a service company. This company is in the field of media-entertainment (it will be called company X, due to confidentiality) and has commit the delivery of technological and trade materials to an external supplier. In this case, the failures of the delivery process are the shipments in stock. Those shipments aren’t delivered at the first attempt and remain in the supplier’s warehouse, often for days.

2. Tools review Strengths and Weaknesses

Designers, during new product development, use some simple tools to investigate and prevent the possible features’ failures. These tools permit them to make a more robust design of a new product and help them to avoid or reduce future technical problems. In this section are described briefly the principal failures’ detecting technique which serve to the purpose of the framework. The first tool is Failure modes and effect criticality analysis-FMECA (US Military Standard, MIL-STD-1629A, 1980; 1983) which was adopted by engineers to ensure that all the potential failures of a new product have been considered and analyzed in terms of failure modes, related causes,

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and possible effects on the customer. (M. Braglia et all 2005). It consist in two sequential phases (Lefayet Sultan Lipol & Jahirul Haq 2011):

- Failure Mode and Effect Analysis (FMEA). It consist in identifying every potential failure mode, the effect of failure and the causes of failures for every features’ component of a product.

- Criticality Analysis (CA). In this step, the failures are evaluated with three components: Severity (S), Occurrence (O) and Detectability (D). At the end, it can be obtained a rank of priority by multiplying these components to produce a risk priority number (RPN).

Derived directly to FMECA is the Dysfunction mode and effects critical analysis –DMECA (M. Bertolini et al. 2006) which analyze the potential failures of the elementary activities of a process. It consist of the same two phases:

- Dysfunction Mode and Effects Analysis (DMEA). It consist in identifying every potential dysfunction mode, the effect of dysfunction and the causes of dysfunction for each elementary activity constituting the process;

- Criticality Analysis (CA). The dysfunction modes are evaluated with three components: Severity (S), Occurrence (O) and Detectability (D). At the end, it can be obtained a rank of priority by multiplying these components to produce a risk priority number (RPN).

These tools can be applied at every product or process in every business field and permit to obtain a quantitative rank of the failures. They don’t consider though the voice of customer or the degree of importance of the effects of failures during the evaluation of the failures modes. A tool that overcome to this lack is the House of Reliability-HoR, which combined the FMEA phase with the Quality Function Deployment, to consider the voice of customer at the same time with the failures analysis. This tool formally follows the structure and shape of the “house of quality” with rooms and roof, whereas its goals are deeply different (M. Braglia et all 2005). The principal tasks of the QFD is describing and scoring customer requirements (CRs); determining design requirements (DRs), the relationship between CRs and DRs, the correlations among CRs, and the correlations among DRs. Finally, the DRs can be scored by these assessments in new product development (Wen-Chang Ko 2015). The task of the HoR, instead, is describing and scoring features’ failure effects; determining failures’ causes, the relationship between effects and causes and the correlations among failures’ causes. Finally, the failures’ causes can be scored and corrective actions can be implemented. Therefore, the HoR permit to obtain a weighed scored

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of failures causes by the degree of importance of the failures effects, assigned by customers. Designers thus can concentrate their efforts and budget for the most important features’ failure effects, and can reduce significantly design phase.

The weakness of this tool is the difficult application of all its steps for a process. In particular calculating the correlations between the causes of dysfunctional modes of a process is long and not always possible.

An easier tool for investigating the relationship between causes is the Fault Tree Analysis- FTA. Fault trees are a graphical method that model how failures propagate through the system, i.e., how component failures lead to system failures (Enno Ruijters and Mariëlle Stoelinga 2015). Fault trees are directed acyclic graph consisting of two types of nodes: events and gates. An event is an occurrence within the system, typically the failure of a subsystem down to an individual component. Events can be divided into basic events (BEs), which occur spontaneously, and intermediate events, which are caused by one or more other events. The event at the top of the tree, called the top event (TE), is the event being analyzed, modeling the failure of the (sub)system under consideration.

The strength of this tool are the graphical trees whom are fast to build and permit to understand

immediately the relationship between failures. On the other hand, the trees don’t consider the failure’s effects or their degree of importance for customers.

The methodology prosed in this framework is the combination of the strengths of tool for obtaining a complete failures analysis for a process, considering both the effects’ degree of importance and the relationship between failures’ causes.

3. How to apply the three tools

In this section is shown step-by-step (Figure 1) how to apply the described tools for analyzing a process’ failures. It has been applied for identifying and evaluating the possible causes of failures for delivery process in company X. This organization is one of the leader company in the media-entertainment sector and has almost 3 million customers. Each customer needs technological materials to watch programs on the tv and has to pay a monthly subscription. So, for providing materials to customers the company has commit the delivery activities to an external supplier. The supplier has to stock, prepare and deliver materials respecting the contractual conditions, in particular the delivery time (less than 4 working days). The failures of the process are the

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shipments in stock. Those shipments aren’t delivered at the first attempt and remain in the supplier’s warehouse, often for several days. They can also become returned shipment, i.e. the customer doesn’t receive the materials but the company has already payed the delivery service to the supplier. This situation is the worst scenario because the customer isn’t able to watch tv programs and for the company it’s a monetary loss but more important an image damage.

Figure 1. Methodology steps

3.1 Dysfunction mode and effects critical analysis (DMECA)

The first step of DMECA is the deployment of the analyzed process to identify each elementary activity. For the examined case it has been done with a Process Breakdown Structure (Figure 2), like M. Bertolini et all (2005) did in their framework.

The second step is identifying dysfunction modes, dysfunction effects and dysfunction causes for each elementary activity. For this step can help building a table that have six column: activity ID, activity, dysfunction cause ID, dysfunction cause, dysfunction mode and dysfunction effect. In figure 3 and 4 there’s an example for some activities of the delivery process, in particular for whom can generate shipping in stock effect. The dysfunction effects are simple the outcomes provided by couriers that company X wants to avoid or at least reduce. The dysfunction modes and causes are been identified by the members of logistics team with a brainstorming session. Each cause can produce more effects and each effect can derive from more causes. For this reason, the relationship between the causes have to be investigated for arriving to primary causes, the ones from which derived the others. It can be decided a scale of priorities for the

1. DMECA

•Deployement of the process (Process Breakdown Structure) •Indentification of dysfunction modes, effects and causes 2. Fault tree analysis

•Construction of the fault trees 3. HoR

•Evaluation of effects' degree of importance •Construction of the causes-effects relationship matrix •Evaluation of the relationships

•Adaptation of the convertion tables for Occurrence and Detectability •Evaluation of Occurrence and Detectability for each dysfunction's cause •Calculation of the RPN for each cause

4. Creation of the dysfunction causes ranking 5. Proposal of the corrective actions

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effects to concentrate time and operative efforts. In the examined firm case, the logistics team decided to deepen the study for the shipping in stock because these effects create more work for several company teams and they can produce shipment returns to central warehouse for not being delivered to customers. For the company is the principal failure to avoid because it represent a waste of money and produce also customer claims to manage.

Figure 2. Delivery process breakdown structure

1. Creation of a sales order

1.1 The customer enters his personal data on the company

website

1.2 Data are saved in the company data base

1.3 Data are processed by company's informative system 2. Creation of a shipping order 2.1 Verifying stock availability 2.2 Warehouse unloading 2.3 Shipping order sending to the central

warehouse 3. Shipment preparation in the central warehouse 3.1 Shipping order reception

3.2 Materials picking & packaging 3.3 Transport document printing 3.4 Shipment sending to Courier service 4. Delivery to customer 4.1 Shipment reception 4.2 Van loading 4.3 Shipment delivery 4.4 Outcomes sending to central warehouse 5. Monitoring shipment tracking 5.1 The central warehouse receives shipment outcomes from courier service

5.2 The central warehouse sends shipment outcomes to the company 5.3 Shipment outcomes processing 5.4 Customers claims management

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Figure 3. Table of dysfunction modes, effects and causes

ID ACTIVITY ID DYSFUNCTION CAUSE DYSFUNCTION MODE DYSFUNCTION EFFECT

1.1 The customer enters his personal data on the company website

1.1.1 Website of the company isn’t user friendly

The customer enter wrong or incomplete data in the company website

Shipping in stock for wrong address

1.1.2 The customer types wrong

data due to his fault

1.2 Data are saved in the company data base

1.2.1 Informative system malfunction

Data aren’t saved or saved wrong or incomplete

Shipping in stock for wrong address, shipping in stock for missing addressee, shipping in stock for addressee’s refusal 1.3 Data are processed by company's informative system 1.3.1 Company’s informative system malfunction

Loss or compromised data Shipping in stock for wrong address, shipping in stock for missing addressee, shipping in stock for addressee’s refusal

3.1 Shipping order reception

3.1.1 Company’s informative system malfunction

The central warehouse receives wrong or incomplete shipping order

Shipping in stock for wrong address, shipping in stock for addressee’s refusal

3.2 Materials picking & packaging

3.2.1 Wrong materials packaging Customer receives wrong or incomplete materials

Shipping in stock for addressee’s refusal 3.3 Transport document printing 3.3.1 Company’s informative system malfunction

Transport document is printed wrong or incomplete

Shipping in stock for wrong address, shipping in stock for addressee’s refusal

3.4 Shipment sending to Courier service

3.4.1 Materials have been damaged during the trip to the courier for major force causes (not due to central warehouse)

Materials arrive damaged to courier

Shipping in stock for damage

3.4.2 Materials have been sent

damaged to the courier for central warehouse faut

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Figure 4. Table of dysfunction modes, effects and causes

ID ACTIVITY ID DYSFUNCTION CAUSE DYSFUNCTION MODE DYSFUNCTION EFFECT

4.3 Shipment delivery

4.3.1 Adverse weather conditions

Courier can’t physically arrive to customer’s address

Shipping in stock for major force

4.3.2 Patronal feast, demonstrations, strikes, etc

4.3.3 Deceased addressee Nobody accepts the shipment Shipping in stock for major force, shipping in stock for missing addressee

4.3.4 Addressee impossible to

be found

Nobody accepts the shipment Shipping in stock for missing addressee

4.3.5 Addressee is absent when

the courier delivers the shipment

Nobody accepts the shipment Shipping in stock for missing addressee

4.3.6 Addressee relocated Nobody accepts the shipment Shipping in stock for missing addressee, shipping in stock for wrong address

4.3.7 Courier has a wrong or

incomplete address

Courier can’t find customer’s address

Shipping in stock for wrong address

4.3.8 Unknown addressee Nobody accepts the shipment Shipping in stock for wrong address, shipping in stock for addressee’s refusal, shipping in stock for missing addressee

4.3.9 Addressee has already

received the materials

Addressee refuses the shipment

Shipping in stock for addressee’s refusal

4.3.10 Addressee doesn’t want

materials for personal reasons

Addressee refuses the shipment

Shipping in stock for addressee’s refusal

3.2 The Fault Tree Analysis (FTA)

From this tool the only step to do are the Fault Trees. They are a simple graphical method to understand the relationship between causes, both father/son relationships and AND/OR relationship. The dysfunction effect is the top unwanted event to avoid or reduce and can be produced by a combination of dysfunction causes from different levels. The leaves of the trees are the father causes that generate the others and conduct to the top event. The relationships between causes at the same level are the AND/OR relationships. The AND means that the

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superior level derived by a set of some causes whom occur together, the OR instead means that it derived from the occurrence of a cause or another but not by a set. The effects and the causes are been found with the previous steps of DMECA. In figure 5, 6 and 7 are showed the fault trees for the three more numerous shipping in stock effects: shipping in stock for wrong address, shipping in stock for addressee’s refusal and shipping in stock for missing addressee.

Figure 5. Fault tree of shipping in stock for wrong address

SHIPPING IN STOCK FOR WRONG ADDRESS

OR

Unknown addressee

OR

Addressee relocated

Company database isn't uploaded

Courier has a wrong or incomplete address

Courier can’t find customer’s address

Address isn't easy to find for structure of the land

itself

AND

Courier has a wrong or incomplete address Addressee impossible to be found OR Courier has wrong/incomplete phone number Addressee doesn't answer to courier's phone calls

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Figure 6. Fault tree of shipping in stock for addressee’s refusal

SHIPPING IN STOCK FOR ADDRESSEE'S REFUSAL

OR

Unknown addressee

OR

Courier has a wrong or incomplete address

OR

Company’s informative system malfunction

The address is saved wrong/incomplete in the company's database

The customer enter wrong or incomplete data in the company

website

OR

The customer types wrong data due to his

fault

Website of the company isn’t user

friendly Addressee relocated

Company database isn't uploaded

Addressee doesn’t want materials

Addressee can't accetp materials for personal problems,not due to the

company misunderstood contractual conditions OR Customer received wrong/incomplete information during conctractual propose Customer didn't understand all the information during conctractual propose

Damaged materials

OR

Materials have been damaged by courier

carrier

Materials have been sent damaged for a central warehouse fault

Materials have been damaged during the trip

due to major force causes

Deceased addressee Wrong/incomplete _materials

OR

Wrong materials packaging

The central warehouse receives wrong or incomplete shipping order OR Company’s informative system malfunction wrong/incomplete shipping order due to

company Addressee has already received the materials

Company’s informative system malfunction

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Figure 7. Fault tree of shipping in stock for missing addressee

3.3 The House of Reliability (HoR)

Each effect has a different degree of importance, due to the occurrence of happening and to the damage which causing to the company. The House of Reliability so can be used to conduct the Criticality Analysis (CA) for considering both the effects’ degree of importance and the relationship between each effect and each cause. In particular, it used the relationship matrix

SHIPPING IN STOCK FOR MISSING ADDRESSEE OR Unknown addressee OR

Courier has a wrong or incomplete address

OR

Company’s informative system malfunction

The address is saved wrong/incomplete in

the company's database

The customer entered wrong or incomplete data in the company

website

OR

The customer types wrong data due to his

fault

Website of the company isn’t user

friendly

Addressee relocated

AND

Addressee is absent when the courier delivers the shipment

Nobody accepts the shipment

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between failure’s effects and failure’s causes. The roof is replaced by the previous step with Fault trees, because calculating the correlation between causes is difficult for a process and it would be a very long and activity that needs lots of information, not always available. That’s because correlation can depend from several factors, both internal and external from the company, whom are not always immediate to discover or identify.

The lines of the matrix represents the dysfunction effects, identified with the DMECA, and the columns are the dysfunction causes, identified with the leaves of the fault trees (Figure 8).

Figure 8. Structure of HoR: a) Dysfunction effects, b) Dysfunction causes, c) Effects’ degree of importance, d) Correlation matrix.

The degree of importance of each effect is obtained like a weighted average of the individual mark assigned to the effect by the logistics team components. Each component analyzed the various effects and assigned a mark from 1 (least important effect) to 5 (the more important effect) basing on his own work experience and on shipment historical data (i.e. the number of each type of shipping in stock). The results are showed in Table 1.

Table 1. Effects’ degree of importance

Shipping in stock Degree of importance

Member 1 Member 2 Member 3 Member 4 Mark average

For major force 3 1 1 1 1,5

For missing addressee 9 9 9 9 9

For damage 1 1 1 1 1

For wrong address 9 9 9 9 9

For addressee’s refusal 9 3 9 9 7,5

d b

c a

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For building the relationship matrix each effect-cause relationship is been numerically defined by a logarithmic scale, in particular:

- 1 for weak relationship;

- 3 for medium grade relationship; - 9 for strong relationship.

The logarithmic scale permits to obtain a well defined scale of priorities because the strong relationships emerge sharply from the others.

The next step to be done is the evaluation of the priorities to create a rank of the dysfunction causes by calculating the Risk Priority Number (RPN). This is a criticality parameter obtained by the combination of severity of the effects, probability that the effect occurs and chances that it can be detected during the monitoring of the process. The Severity value is obtained automatically from the HoR by a weighed sum of the relationship value with the effect degree of importance:

S = (r1*d1)+(r2*d2)+…+(rn*dn)

Where r1,r2,…,rn are the relationship values and d1,d2,…,dn are the effects’ degree of importance.

For example the Severity value for the cause “Addressee relocated” is calculated like this: S = (r2*d2)+(r8*d8) = (3*9)+(9*9) = 108

In figure 9 there’s the HoR built for the delivery process.

The values of the probability to occur (Occurrence) and the chance to be detected (Detectability) can be obtained by tables whom convert qualitative judgments in numerical values (see, for example Bertolini et al., 2006, Bertolini, Bevilaqua and Massini, 2006, MIL-STD-1629A, 1980-1983). These conversion tables have to be fitted to the specific organization process, so the number of classification levels can vary from a process to another. For the company X it has been decided to build 5 levels of Occurrence and 5 levels of Detectability to simplify the evaluation of failure’s effects (Table 2 and 3). Furthermore, more levels could have brought to a too much detailed classification, which didn’t fit well to the process in exam.

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Logistics team members, then, assigned a level of Occurrence and Detectability to each cause by a brainstorming session, in which judgements and levels were discussed for arriving to a shared vision.

The RPN, so, can be calculated by multiplying the values of Severity, Occurrence and Detectability:

RPN = S x O x D.

For example the RPN for the cause “Addressee relocated” is: RPN = 108 x 5 x 5 = 2.700.

Table 2. Conversion table for the occurrence factor

OCCURRENCE Qualitative/linguistic evaluation of the

dysfunction occurrence

Number of shippings in stock O

High >10% of cleared shipments 5

Moderate 10% of cleared shipments 4

Low 7-8% of cleared shipments 3

Remote 5-6% of cleared shipments 2

Irrelevant <5% of cleared shipments 1

Table 3. Conversion table for the detectability factor

DETECTABILITY Qualitative/linguistic evaluation of the

dysfunction detection

Description D

Impossible Customers detects dysfunction and call to claim 5

Very low The information system is damaged and

shipments' tracking isn't updated

4

Low Members of distribution team detect dysfunction

after the shipment has been cleared less than 72h

3

Moderate Members of distribution team detect dysfunction after control

2

High Dysfunction detected after the shipment has been

cleared (extra informations are communicated to distribution team )

20

Figure 9. The House of Reliability for the delivery process

. Deg ree s o f im po rt an ce Co ur ier c an ’t ph ysic all y ar rive to cu st om er’s ad dr ess fo r a dve rs wea th er c on dit ion s Co ur ier c an ’t ph ysic all y ar rive to cu st om er’s ad dr ess fo r P at ro na l fea st , dem on st ra tio ns , s tr ikes , e tc Dec eas ed a dd res see Th e c us to mer typ es w ro ng da ta du e to his fa ult Web sit e o f t he co mp an y isn ’t us er f rien dly Cu st om er r eceive d w ro ng /in co mp lete inf or ma tio n d ur ing co nc tr ac tu al p ro po se Ad dr ess ee r eloc at ed Co mp an y’s inf or ma tive sys tem ma lfu nc tio n Co ur ier h as a w ro ng or inc om plet e a dd res s Co ur ier h as wr on g/ inc om plet e p ho ne nu mb er Ad dr ess ee d oes n't an sw er t o c ou rier 's ph on e c all s Ad dr ess ee c an 't ac cet p m at eria ls f or per so na l pr ob lems ,n ot du e to th e c om pa ny wr on g/ inc om plet e s hip pin g o rd er d ue to co mp an y Wr on g m at eria ls p ac kag ing No bo dy a cc ept s t he sh ipm ent fo r t he ad dr ess ee Ad dr ess ee is ab sen t w hen th e c ou rier deli ver s t he sh ipm ent Ma ter ials ha ve b een da ma ged du rin g t he tr ip b y a c ou rier vec to r f au lt Ma ter ials ha ve b een da ma ged du rin g t he tr ip f or ma jo r f or ce ca us es ( no t d ue to co ur ier v ecto r) Sh ipp ing in st oc k f or m ajo r f or ce 1,5 9 9 1 Sh ipp ing in st oc k f or m iss ing ad dr es see 9 3 3 3 3 9 9 9 9 Sh ipp ing in st oc k f or da m ag e 1 9 9 Held fo r p ick-up 1,5 Sh ipp ing in st oc k f or w ro ng ad dr es s 9 9 9 9 9 9 9 3 Sh ipp ing in st oc k f or ad dr es see ’s r ef us al 7,5 3 9 9 3 9 9 9 3 3 3 3 13 ,5 13 ,5 49 ,5 81 14 8,5 67 ,5 108 13 0,5 108 162 108 67 ,5 67 ,5 67 ,5 10 3,5 10 3,5 31 ,5 33 Oc cu rren ce 1 1 1 2 3 2 5 4 5 4 4 3 1 1 5 5 2 1 Det ec ta bil ity 1 1 5 5 4 4 5 3 3 3 5 5 4 4 5 5 5 5 RP N 13 ,5 13 ,5 24 7,5 810 1782 540 2700 1566 1620 1944 2160 10 12 ,5 270 270 25 87 ,5 25 87 ,5 315 165 15 15 13 9 5 10 1 7 6 4 3 8 12 12 2 2 11 14 Ra nk Sev er ity Dys fu nc tio na l e ffec ts (Sh ipp ing in st oc k) Dys fu nc tio na l ca us e

21 3.4 Dysfunction causes ranking

The fourth step to be done is the ranking of the causes to see the more impactful for the process (figure 10). The cause in first position has the highest RPN and the cause in last position has the lowest. If two or more causes have the same RPN, in the ranking goes first the cause which have the Severity value superior and if it is not possible they go in the same position. The company at this point has to decide a RPN tolerability threshold, above which are the intervention priorities.

Figure 10. Rank of the dysfunction causes

RANK CAUSE RPN

1 Addressee relocated 2700

2 Nobody accepts the shipment for the addressee 2588

2 Addressee is absent when the courier delivers the shipment 2588

3 Addressee doesn't answer to courier's phone calls 2160

4 Courier has wrong/incomplete phone number 1944

5 Website of the company isn’t user friendly 1782

6 Courier has a wrong or incomplete address 1620

7 Company’s informative system malfunction 1566

8 Addressee can't accetp materials for personal problems,not due to the company 1013

9 The customer types wrong data due to his fault 810

10 Customer received wrong/incomplete information during conctractual propose 540 11 Materials have been damaged during the trip by a courier vector fault 315

12 wrong/incomplete shipping order due to company 270

12 Wrong materials packaging 270

13 Deceased addressee 248

14

Materials have been damaged during the trip for major force causes (not due to courier

vector) 165

15

Courier can’t physically arrive to customer’s address for Patronal feast, demonstrations,

strikes, etc 14

22 3.5 Corrective actions proposition

At this point some corrective actions can be proposed and implemented to reduce or avoid the causes and so on the failure’s effects. In the case study the logistics team decided to fix the RPN threshold at 1600, so corrective actions will be proposed only for the first six cause in the ranking. One solution for the causes 1,4 and 6 could be to control and update the company database 1 or 2 times in a year, now this activity is done only after the shipping in stock and not every time. For the causes 2, 3 and 5 could be, for example, to insert two more required fields, like an alternative delivery address and a space to write some additional notes for the address (condominium floor, side of the way, some points of reference, etc). An other propose is to implement delivery time slot or the delivery on Saturday but it’s more difficult to apply. It would change the contract with the supplier and consequently the price of the service.

4. Conclusions

In the services field, in particular when the organization commits some process activities to an external supplier, the measure of process efficiency is difficult and the evaluation of the possible risks is fundamental. This paper introduces a methodology created with existent tools to manage risk management for every process. Following the steps allows user to (i) identify and evaluate failures for each activity in a process and (ii) to define a priority ranking for the implementation of the corrective actions. It’s a systematic approach for studying failure causes and the relationships between them. The tools used are well known and usually used in manufacturing companies, during product development, but they can be fitted almost easily to a process. The idea of combining this three tools is to find a simple methodology which has a relevant graphic part that permits easily to find and understand the results.

From a theoretical point of view, it would be desirable to establish modes more objectively to evaluate the Occurrence and Detectability parameters than the use of questionnaire and simple evaluation of judgements. It would be also interesting to apply this methodology at other processes of the same company to investigate if a failure can be caused by an other process.

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