Approach for the implementation of resource analysis methods in learning factories

Figures & data

Table 1. Comparison of relevant design approaches and respective steps.

Tisch et al.	Plorin et al.	Doch et al.	Karre et al.
1. Requirement analysis (including organizational environment, organizational targets and target group)	1. Profiling of the existing learning environment	1. Requirement analysis (including definition of scope and training goals, determination of needed infrastructure)	1. Preparation (including research findings)
2. Definition and operationalization of learning targets (intended competencies)	2. Derivation of the use cases	2. Conceptualisation (focus training modules)	2. Analysis (including future requirements and system of objectives)
3. Configuration and Design of technical and didactical infrastructure (including factory elements and learning methods)	3. Derivation of the learning modules	3. Configuration and implementation (including concretion and execution of training modules, continuous adjustment)	3. Opportunity identification (promising use cases for industry 4.0)
	4. Matching with competencies of the learning environment		4. Evaluation (prioritization and development of roadmap)
	5. Structure of the competence profile of the target groups		5. Implementation (development of action plan)
	6. Configuration and parametrization of the learning modules
	7. Design of the learning environment
	8. Integration into the existing learning environment

Figure 1. Developed process for the extension of learning factories regarding new topics.

Figure 2. The considered methods in the framework for increasing resource efficiency by Weyand, Rommel, et al. (2021).

Table 2. Description of the considered methods.

Method	Description
Life Cycle Assessment (LCA)	LCA is an accounting method that considers the environmental impact of a product from the extraction of raw materials, through manufacturing and use, to disposal. The impact can be quantified in different impact categories, one example being climate change. The assessment is done in four steps, one being the life cycle inventory analysis (LCIA) in which data about the resource consumption is acquired as detailed as possible. To get the needed impact factors related to the considered resources, databases can be used. (Deutsches Institut für Normung e.V. DIN, 2021a, 2021b)
Carbon Footprint (CF)	The CF is a special form of LCA, where only the global warming potential quantified in CO2-equivalents is the considered impact category. The CF can be deducted for products (PCF, (DIN, 2019a)) or companies (CCF (DIN, 2019b)) and divided into direct (Scope 1) and indirect emissions (Scope 2, Scope 3) according to the standard Greenhouse Gas Protocol. (Smith, 2004; Wiedmann & Minx, 2008)
Material Flow Cost Accounting (MFCA)	MFCA is an analysis method with an integrated economic-ecological approach. A relationship is established between the physical resource variables, such as the materials used in kilogram, and the financial data, such as the purchase price. The results are presented in a material flow model, visualized in specific software in form of a Sankey diagram. (Deutsches Institut für Normung e.V. DIN, 2011; M. Schmidt & Nakajima, 2013)
Checklists	Checklists can be used to analyze a production site based on different listed aspects or questions. This method does not include measurements, but due to many different checklists available and the possibility to set up own checklists tailored for the specific forms of production sites, it can lead to a high number of identified hotspots and possible measures. (Scriven, 2000) Examples of predefined checklists can be found in (Kishita et al., 2010; Umweltbundesamt Ed., 2001)
Energy Value Stream Mapping (EVSM)	EVSM is based on the Value Stream Method (VSM), which distinguishes between value-adding and non-value-adding processes. VSM only considers the material, personnel, machinery and process control. To also include the required energy, the Fraunhofer Institute for Manufacturing Engineering and Automation has further developed the VSM into the Energy Value Stream Mapping, aiming at recording all energy flows occurring at the production site and increasing their efficiency. Visualisation is done in a similar template as used for VSM. (Erlach, 2013)
ABC analysis (ABC)	The ABC analysis is a comparative method. The main focus is not on the detailed analysis of data, but on the prioritization of the respective objects of investigation. The ABC analysis occurs outside of the field of resource efficiency as well, but in this paper, it is applied to the plugged-in power of machines which can be found on the type plate directly at the machines. By comparing these power values with each other, the machines can be rated in A, B or C categories according to their size and respective assumed importance. (Posselt, 2016)
Portfolio Matrix (PM)	The PM is an extension of the ABC analysis, including the utilization time next to the plugged-in power and displaying it in a matrix form, so each quadrant marks a different importance. Machines with high plugged-in power as well as high utilization time are considered the relevant hotspots. (S. Thiede, 2012, p. 137)
Thermal Energy Diagnosis (TED)	TED is a method that reveals potential regarding thermal energy, especially waste heat. In particular, the aim is to avoid the generation of waste heat when it is not necessary or identify possibilities to use it otherwise. The approach is similar to the thermal energy diagnoses in the building sector (Katunsky et al., 2013). In the first step, the temperatures of the component and its surroundings are determined with a thermal imaging camera as it passes through the production process. The temperature curves determined are then transferred to a diagram, which can be used to detect optimization potential, where waste heat can be avoided or used.
Cumulative Energy Demand (CED)	In CED, the entire life cycle of a product is assessed in terms of its primary energy consumption. For this purpose, the cumulative energy consumption of production, use and disposal is added up. Energy consumption should be measured to avoid allocations and inaccuracies (VDI, 2012)
Cumulative Material Demand (CMD)	CMD measures all raw materials that are required for the production of a product over the entire life cycle. This includes all raw materials used in production and transportation, as well as material energy sources. Here as well, measurements are preferred for accurate data acquisition (VDI, 2018).

Figure 3. Approach for rating the hotspot analysis methods.

Table 3. Matrix of efforts and benefits for each method, applied to the ETA Learning Factory at TU Darmstadt (in case of alternatives, default scenario is marked bold).

	Methods
Criteria		LCA	CF	MFCA	Checklist	EVSM	ABC	PM	TED	CED	CMD
Effort	Time effort
	for execution	3.5 months/ 2.5 months	3 months/ 2 months	3 months/ 2 months	0.5 day	2 months/ 1.5 months	1 hour	1 day	0.5 day	2 months/ 1.5 months	3 months/ 2 months
	for initial skill adaption training	2 days/ 3 days	1 day/ 2 days	1 day/ 2 days	1 hour	2 days/ 1 day/ 3 days	0,5 hour	1 hour	0.5 hour	1 day/ 2 days	1 day/ 2 days
	Costs
	for data acquisition	~ 2,500 €/ 1,000 €/	~ 2,500 €/ 1,000 €/	~ 2,500 €/ 1,000 €/	0 €	~ 1,000 € / 0 €	0 €	0 €	~ 500 €/ 0 €	~ 1,000 €/ 0 €	~ 2,500 €/ 1,000 €/
	for evaluation and visualisation	~ 9,000 €/ 4,500 €/	~ 1,300 €/ 0 €	~ 4,500 €/ 0 €	0 €	0 €	0 €	0 €	0 €	0 €	0 €
Benefit	Considered Life Cycle Phase(s)
	production	yes	yes	yes	yes	yes	yes	yes	yes	yes	yes
	product development	yes	yes	yes	yes	no	no	no	no	yes	yes
	other life cycle phases	yes	yes	yes	yes	no	no	no	no	yes	yes
	Considered environmental impact(s)
	electrical energy	yes	yes	yes	yes	yes	yes	yes	no	yes	yes
	thermal energy	yes	yes	yes	yes	no	no	no	yes	yes	yes
	material	yes	yes	yes	yes	no	no	no	no	no	yes
	Quantification
	in kWh	yes	no	yes	no	yes	no	no	yes	yes	no
	in kg	yes	no	yes	no	no	no	no	no	no	yes
	in CO2-equivalents	yes	yes	no	no	no	no	no	no	no	no
	in other environmental impact indicators	yes	no	no	no	no	no	no	no	no	no
	Consideration of financial impact	no	no	yes	no	no	no	no	no	no	no

Table 4. Resulting scale division for each rating criterion.

	0 (○)	0,25 (◔)	0,5 (◑)	0,75 (◕)	1 (●)
Time effort for execution	>3.2 months	>2.4–3.2 months	>1.6–2.4 months	>0.8–1.6 months	0–0.8 months
Time effort for initial skill adaption training	>2.4 days	>1.8–2.4 days	>1.2–1.8 days	>0.6–1.2 days	0–0.6 days
Costs for data acquisition	>2,400 €	>1,800–2,400 €	>1,200–1,800 €	>600–1,200 €	0–600 €
Costs for evaluation and visualisation	>8,000 €	>6,000–8,000 €	>4,000–6,000 €	>2,000–4,000 €	0–2,000 €
Considered Life Cycle Phase(s)
Production	no	-	-	-	yes
Product development	no	-	-	-	yes
Other life cycle phases	no	-	-	-	yes
Considered resources
Electrical energy	no	-	-	-	yes
Thermal energy	no				yes
Material	no	-	-	-	yes
Quantification
in kWh	no	-	-	-	yes
in kg	no	-	-	-	yes
in CO2-equivalents	no	-	-	-	yes
in other environmental impact indicators	no	-	-	-	yes
Consideration of financial impact	no	-	-	-	yes

Figure 4. Examples of different options to get the weighting scale: paired comparison (A) and direct numbers (B).

Table 5. Extract of the competency matrices including respective requirements, developed for each hotspot analysis method.

Life Cycle Assessment (LCA)
Competency	Sub-Competencies		Corresponding Action	Knowledge Base	Requirement for the learning environment
Participants ability to analyse resource consumption	1.1	Participants’ ability to identify the used and relevant resources	List resources used on the considered machines	Knowledge about different types of resources, understanding of the production process	Machines with different resources
	1.2	Participants’ ability to get the consumption of the considered resources	Extraction of needed resource consumption data from different sources, e.g. an environmental management tool	Knowledge about needed data, methods to gather the data	Sensor concept to gather resource consumption data Monitoring concept to display resource consumption data
	…	…	…	…	…
ABC analysis (ABC)
Compe-tency	Sub-Competence		Corresponding Action	Knowledge Base	Requirement for the learning environment
Participants ability to rank machines according to plugged-in power	1.1	Participants’ ability to collect plugged-in power of different machines	Listing the considered machines and assigning respective plugged-in power	Knowledge about production process	Visibility of plugged-in power (extra sign if type plate is not visible for participants)
	1.2	Participants’ ability to rank machines in A-B-C categories according to share on total plugged-in power	Getting the share of the plugged-in power of each machine in relation to total plugged-in power	Knowledge about rule of proportion	Providing calculators for participants
	…	…	…	…	…

Figure 5. Approach for learning factory operators to address resource efficiency methods.

Figure 6. Rating of the methods with adjusted weighting according to the identified requirements and prerequisites in the CiP Learning Factory.

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